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- Decision-Making
  Decision-Making
  - Optimization
    Optimization
    
    Toolboxes & Solvers
    Toolboxes & Solvers
    
    Convex Optimization
    Convex Optimization
    
    CVXPY
    
    CVXPYgen
    
    Disciplined Convex-Concave Programming
    
    ECOS
    
    Embedded SOCP Code Generation
    
    OSQP
    
    Clarabel
    
    CuClarabel
    
    Presolving for GPU-Accelerated First-Order LP Solvers
    
    Nonlinear Optimization
    Nonlinear Optimization
    
    YALMIP
    
    CasADi
    
    CusADi
    
    Learning for CasADi
    
    Markov Decision Processes (MDPs)
    Markov Decision Processes (MDPs)
    
    madupite
    
    Optimality Guarantees for Particle Belief Approximation of POMDPs
    
    Online Planning Algorithms for POMDPs
    
    Black-Box Optimization
    Black-Box Optimization
    
    REMBO
    
    Optuna
    
    Nevergrad
    
    Bayesian Hyperparameter Optimization with BoTorch, GPyTorch and Ax
    
    Bayesian Optimization Is Superior to Random Search for Machine Learning Hyperparameter Tuning
    
    PyHopper
    
    Optimizing with Low Budgets
    
    Automatic Differentiation
    Automatic Differentiation
    
    On Automatic Differentiation
    
    Automatic differentiation in machine learning: a survey
    
    Fast Exact Multiplication by the Hessian
    
    Gradient-Based Optimization of Hyperparameters
    
    Gradient-based Hyperparameter Optimization through Reversible Learning
    
    SoftJAX & SoftTorch
    
    The Elements of Differentiable Programming
    
    Minimax & Game Theory
    Minimax & Game Theory
    
    On General Minimax Theorems
    
    Subgradient Methods for Saddle-Point Problems
    
    A survey of distributed optimization
    
    Elementary Proof for Sion's Minimax Theorem
    
    Learning Without Mixing: Towards A Sharp Analysis of Linear System Identification
    
    The Fragility of Learning LQG Controllers
    
    Zeroth-Order Methods
    Zeroth-Order Methods
    
    Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization
    
    Gradientless Descent: High-Dimensional Zeroth-Order Optimization
    
    A Stochastic Gradient Descent Approach to Design Policy Gradient Methods for LQR
    
    An Introduction to Zero-Order Optimization Techniques for Robotics
    
    An Optimal Algorithm for Bandit and Zero-Order Convex Optimization with Two-Point Feedback
    
    Random Gradient-Free Minimization of Convex Functions
    
    Direct Search & Pattern Search
    Direct Search & Pattern Search
    
    Rosenbrock's Method
    
    Powell's Method
    
    Evolutionary & Swarm Optimization
    Evolutionary & Swarm Optimization
    
    Particle Swarm Optimization
    
    Differential Evolution
    
    Second Order Methods for Bandit Optimization and Control
    
    Small errors in random zeroth-order optimization are imaginary
    
    Stochastic Zeroth-Order Optimization under Strongly Convexity and Lipschitz Hessian: Minimax Sample Complexity
    
    Zeroth-Order Optimization at the Edge of Stability
    
    Zeroth-Order Optimization Finds Flat Minima
    
    Zeroth-Order Randomized Subspace Newton Methods
    
    First-Order Methods
    First-Order Methods
    
    Gradient Method
    
    Steepest Descent
    
    Polyak-Łojasiewicz inequality
    
    Polyak momentum
    
    A Differential Equation for Modeling Nesterov's Accelerated Gradient Method
    
    Adam
    
    Coordinate Descent Algorithms
    
    Analysis and Design of Optimization Algorithms via IQC
    
    On Symplectic Optimization
    
    Conformal Symplectic and Relativistic Optimization
    
    Gradient Descent Converges to Minimizers
    
    How to Escape Saddle Points Efficiently
    
    Steepest Ascent for Optimal Programming
    
    Armijo Rule
    
    A Simple Convergence Proof of Adam and Adagrad
    
    Adam-mini
    
    Adaptive Gradient Methods Converge Faster with Over-Parameterization (but you should do a line-search)
    
    An overview of gradient descent optimization algorithms
    
    Beyond Convexity - Contraction and Global Convergence of Gradient Descent
    
    Convergence Conditions for Ascent Methods
    
    Convergence Conditions for Ascent Methods. II: Some Corrections
    
    Decoupled Weight Decay Regularization
    
    DoG is SGD's Best Friend
    
    Efficient Numerical Algorithm for Large-Scale Damped Natural Gradient Descent
    
    Gradient Descent on Neural Networks Typically Occurs at the Edge of Stability
    
    Gradient Descent Provably Optimizes Over-parameterized Neural Networks
    
    Katyusha
    
    Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition
    
    Momentum-Based Variance Reduction in Non-Convex SGD
    
    On Globally Optimal Stochastic Policy Gradient Methods for Domain Randomized LQR Synthesis
    
    On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization
    
    On the Convergence of Adam and Beyond
    
    Optimizing Neural Networks with Kronecker-factored Approximate Curvature
    
    Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates
    
    Perception-Based Sampled-Data Optimization of Dynamical Systems
    
    Revisiting the Polyak step size
    
    SARAH
    
    Sharpness-Aware Minimization for Efficiently Improving Generalization
    
    Stein-based Optimization of Sampling Distributions in Model Predictive Path Integral Control
    
    Stochastic Gradient Descent Tricks
    
    Catapult mechanism
    
    Universal Sequence Preconditioning
    
    Quasi-Newton Methods
    Quasi-Newton Methods
    
    DFP
    
    A Regularized Limited Memory BFGS method for Large-Scale Unconstrained Optimization and its Efficient Implementations
    
    RES
    
    DDPNOpt
    
    Newton's Method
    Newton's Method
    
    A Note on the Convergence of Newton's Method
    
    Newton's Method for a Rational Matrix Equation Occurring in Stochastic Control
    
    Regularized Newton Method
    
    Super-Universal Regularized Newton Method
    
    A modified Newton method with cubic convergence: the multivariate case
    
    A Regularized Newton Method for Nonconvex Optimization with Global and Local Complexity Guarantees
    
    Beyond Nonconvexity: A Universal Trust-Region Method with New Analyses
    
    Convergence analysis of a regularized Newton method with generalized regularization terms for unconstrained convex optimization problems
    
    Cubic regularized Newton
    
    OPTAMI
    
    Superfast Second-Order Methods for Unconstrained Convex Optimization
    
    The Hessian of tall-skinny networks is easy to invert
    
    Verification of Sequential Convex Programming for Parametric Non-convex Optimization
    
    Trust Region Methods
    Trust Region Methods
    
    Levenberg-Marquardt
    
    Recent advances in trust region algorithms
    
    Halley's Method and High-Order Methods
    Halley's Method and High-Order Methods
    
    Multivariate Halley method
    
    Super-Halley method
    
    Generalized Halley method
    
    New recurrence relations for Chebyshev method
    
    Proximal Methods
    Proximal Methods
    
    FISTA
    
    Proximal Algorithms
    
    Stochastic Optimization
    Stochastic Optimization
    
    Enhancing Sparsity by Reweighted L1 Minimization
    
    When Does SGD Escape Local Minima?
    
    SGD Input-to-State Stability
    
    Infinite-Horizon Policy-Gradient Estimation
    
    A Stochastic Approximation Method
    
    Accelerating Stochastic Gradient Descent using Predictive Variance Reduction
    
    Making SGD Parameter-Free
    
    Minimal Variance Sampling in Stochastic Gradient Boosting
    
    PAGE
    
    Robust Optimization
    Robust Optimization
    
    Mean Robust Optimization
    
    Convex Optimization
    Convex Optimization
    
    Linear Programming
    Linear Programming
    
    Probability of Unique Integer Solution to a System of Linear Equations
    
    Quadratic Programming
    Quadratic Programming
    
    Automatic Generation of Explicit Quadratic Programming Solvers
    
    General Convex Optimization
    General Convex Optimization
    
    Disciplined Convex Programming
    
    Frank-Wolfe Algorithm
    
    CvxCluster
    
    Learning Parametric Convex Functions
    
    Geometric Median in Nearly Linear Time
    
    Online Convex Optimization
    Online Convex Optimization
    
    No-Regret Algorithms for Unconstrained Online Convex Optimization
    
    Nonlinear Programming
    Nonlinear Programming
    
    Disciplined Nonlinear Programming
    
    Global Solutions to Non-Convex Functional Constrained Problems with Hidden Convexity
    
    Combinatorial Optimization
    Combinatorial Optimization
    
    Held-Karp Dynamic Programming
    
    Dynamic Programming Treatment of the Travelling Salesman Problem
    
    The traveling salesman problem: An overview of exact and approximate algorithms
    
    Assignment Problems
    Assignment Problems
    
    Hungarian algorithm
    
    Munkres algorithm
    
    Jonker-Volgenant algorithm
    
    QuickMatch
    
    Graph Search
    Graph Search
    
    Dijkstra's algorithm
    
    Bellman-Ford algorithm
  - Motion Planning
    Motion Planning
    
    Path Planning
    Path Planning
    
    Geometric Planning
    Geometric Planning
    
    Fundamentals
    Fundamentals
    
    Spatial Planning: A Configuration Space Approach
    
    Potential Fields
    Potential Fields
    
    Artificial Potential Field
    
    Smooth Collision-Free Feedback Laws
    
    Graph Search
    Graph Search
    
    Incremental A*
    
    HPA*
    
    LPA*
    
    Smac Planner
    
    Probabilistic Roadmap (PRM)
    Probabilistic Roadmap (PRM)
    
    PRM
    
    Deterministic Sampling-Based Motion Planning
    
    Efficient high-quality motion planning by fast all-pairs r-nearest-neighbors
    
    Enhancing Sampling-based Planning with a Library of Paths
    
    Generating Diverse Trajectories Using Roadmap Search and Sampling-Based Motion Planning
    
    Rapidly Exploring Random Trees (RRT)
    Rapidly Exploring Random Trees (RRT)
    
    RRT
    
    RRT-Connect
    
    EET
    
    RRT*
    
    RRT* theory correction
    
    Anytime RRT*
    
    BT+RRT*
    
    RRT*-Connect
    
    RRT#
    
    FMT*
    
    Informed RRT*
    
    BIT*
    
    RABIT*
    
    PI-RRT*
    
    Informed RRT*-Connect
    
    Sliding Window Informed RRT*
    
    FCIT*
    
    Spline-based RRT
    
    Continuous-Curvature Target Tree
    
    BIT*
    
    BITKOMO
    
    Improving Motion-Planning Algorithms by Efficient Nearest-Neighbor Searching
    
    Edge Nearest Neighbor
    
    Integrating asymptotically-optimal path planning with local optimization
    
    Geometry-Aware Sampling-Based Motion Planning on Riemannian Manifolds
    
    ST-RRT*
    
    GPU Parallelized Planning
    GPU Parallelized Planning
    
    GMT*
    
    Kino-PAX
    
    Kino-PAX+
    
    pRRTC
    
    cpRRTC
    
    cuRobo
    
    cuTAMP
    
    Dynamic Replanning
    Dynamic Replanning
    
    RRTX
    
    RT-FMT
    
    Revisiting Replanning from Scratch: Real-Time Incremental Planning with Fast Almost-Surely Asymptotically Optimal Planners
    
    Constrained Motion Planning
    Constrained Motion Planning
    
    Vectorizing Projection in Manifold-Constrained Motion Planning for Real-Time Whole-Body Control
    
    Collision Detection & Proximity Queries
    Collision Detection & Proximity Queries
    
    Incremental Distance Calculation
    
    SSV
    
    GJK
    
    A Fast and Robust GJK Implementation for Collision Detection of Convex Objects
    
    Collision-Affording Point Trees
    
    OBBTree
    
    Path Generation
    Path Generation
    
    Lines & Arcs
    Lines & Arcs
    
    Dubins Paths
    
    Reeds-Shepp Paths
    
    Markov-Dubins with Acceleration
    
    Clothoids (linear curvature)
    Clothoids (linear curvature)
    
    SCC Paths
    
    CC Steer
    
    Generalized Clothoids (nonlinear curvature)
    Generalized Clothoids (nonlinear curvature)
    
    Cubic Curvature Polynomials
    
    Sharpness Continuous path
    
    Fast and Accurate G1 Fitting of Clothoid Curves
    
    G2 Hermite Interpolation with Clothoids
    
    Sharpness Continuous Path optimization and Sparsification for Automated Vehicles
    
    Polynomials & Splines
    Polynomials & Splines
    
    Quintic G2 Splines
    
    Quintic Bezier Splines
    
    Quintic Bezier Curve Path Planning
    
    Bézier clipping is quadratically convergent
    
    Linear-time geometric algorithm for evaluating Bézier curves
    
    MINVO Basis: Finding Simplexes with Minimum Volume Enclosing Polynomial Curves
    
    Path Optimization
    Path Optimization
    
    Path Shortcutting
    Path Shortcutting
    
    Creating High-quality Paths for Motion Planning
    
    Anytime Solution Optimization for Sampling-Based Motion Planning
    
    Benchmarking Shortcutting Techniques for Multi-Robot-Arm Motion Planning
    
    Path Smoothing
    Path Smoothing
    
    CCMA
    
    Elastic Bands
    
    Collision-Free and Curvature-Continuous Path Smoothing In Cluttered Environments
    
    Smooth Feedback Motion Planning with Reduced Curvature
    
    Gradient-based Path Optimization
    Gradient-based Path Optimization
    
    CHOMP
    
    Sample-based Path Optimization
    Sample-based Path Optimization
    
    STOMP
    
    Trajectory Planning
    Trajectory Planning
    
    Kinodynamic Planning
    Kinodynamic Planning
    
    Trajectory Planning
    
    Rapidly Exploring Random Trees (RRT)
    Rapidly Exploring Random Trees (RRT)
    
    Kinodynamic RRT
    
    CL-RRT
    
    Kinodynamic RRT*
    
    Linear Kinodynamic RRT*
    
    AQR-RRT
    
    LQR-trees
    
    LQR-RRT*
    
    Optimal Sampling-Based Motion Planning under Differential Constraints: the Drift Case with Linear Affine Dynamics
    
    RRT*_MotionPrimitives
    
    BB-RRT
    
    iDb-RRT
    
    AkinoPDF
    
    Completeness of Randomized Kinodynamic Planners with State-based Steering
    
    Probabilistic completeness of RRT for geometric and kinodynamic planning with forward propagation
    
    FDSPC
    
    TB-RRT
    
    A novel RRT extend function for efficient and smooth mobile robot motion planning
    
    DR-RRT
    
    RANS-RRT*
    
    Efficient Nearest-Neighbor Search for Dynamical Systems with Nonholonomic Constraints
    
    Kinodynamic motion planning: connecting exploration trees using trajectory optimization Methods
    
    Optimal motion planning with the half-car dynamical model for autonomous high-speed driving
    
    Randomized Kinodynamic Motion Planning with Moving Obstacles
    
    Search-based Motion Planning for Quadrotors using Linear Quadratic Minimum Time Control
    
    StaGE
    
    Expansive Space Trees (EST)
    Expansive Space Trees (EST)
    
    EST
    
    Guided EST
    
    Stable Sparse Tree (SST)
    Stable Sparse Tree (SST)
    
    SST*
    
    Meta Algorithms
    Meta Algorithms
    
    AO-x
    
    AORRTC
    
    Planning with Graphs of Convex Sets (GCS)
    Planning with Graphs of Convex Sets (GCS)
    
    SPP-GCS
    
    GCS
    
    fastpathplanning
    
    SCS
    
    Augmented GCS
    
    Augmented GCS for TSP
    
    Trajectory Generation
    Trajectory Generation
    
    TEB
    
    Minimum Snap Trajectory Generation and Control for Quadrotors
    
    Minimum Jerk Trajectory Generation for Differential Wheeled Mobile Robots
    
    Aggressive flight of fixed-wing and quadrotor aircraft in dense indoor environments
    
    Dynamic Movement Primitives in Robotics: A Tutorial Survey
    
    Robust and Efficient Quadrotor Trajectory Generation for Fast Autonomous Flight
    
    Trajectory Optimization
    Trajectory Optimization
    
    Model Predictive Sampling-Based Control
    Model Predictive Sampling-Based Control
    
    Cross-Entropy Motion Planning (CEM)
    Cross-Entropy Motion Planning (CEM)
    
    Cross-Entropy Motion Planning
    
    Model Predictive Path Integral Control (MPPI)
    Model Predictive Path Integral Control (MPPI)
    
    IT-MPC
    
    MPPI
    
    Model Predictive Path Integral Control using Covariance Variable Importance Sampling
    
    Model Predictive Path Integral Control: Theoretical Foundations and Applications to Autonomous Driving (Grady Williams PhD Dissertation)
    
    Tsallis VI-SOC
    
    C-Uniform MPPI
    
    CU-MPPI
    
    Biased-MPPI
    
    Low-pass MPPI
    
    TC-MPPI
    
    VIMPPI
    
    Interaction-Rich MPPI
    
    DBaS-Log-MPPI
    
    Multi-Modal MPPI
    
    TD-CD-MPPI
    
    BC-MPPI
    
    Improving MPPI for High-Inertia Industrial Vehicles
    
    Low Frequency Sampling in Model Predictive Path Integral Control
    
    Path Integral Control in Gaussian Belief Space for Partially Observed Systems
    
    PA-MPPI
    
    Variance-Reduced Model Predictive Path Integral via Quadratic Model Approximation
    
    Dynamic Risk-Aware MPPI for Mobile Robots in Crowds via Efficient Monte Carlo Approximations
    
    Model Predictive Path Integral Control as Preconditioned Gradient Descent
    
    Recent Advances in Path Integral Control (Survey)
    
    Path Integral Particle Filtering for Hybrid Systems via Saltation Matrices
    
    Sampling-Based Control via Entropy-Regularized Optimal Transport
    
    Uncertainty Guided Exploratory Trajectory Optimization for Sampling-Based Model Predictive Control
    
    On Surprising Effects of Risk-Aware Domain Randomization for Contact-Rich Sampling-based Predictive Control
    
    DROP
    
    Model Predictive Trees
    Model Predictive Trees
    
    MPT
    
    MPTree
    
    Optimizing Trajectory-Trees in Belief Space: An Application from Model Predictive Control to Task and Motion Planning
    
    Model Predictive Contouring Control (MPCC)
    Model Predictive Contouring Control (MPCC)
    
    MPCC (RC Cars)
    
    MPCC (Articulated Vehicles)
    
    Model predictive contouring control
    
    Iterative Linear Quadratic Regulator (iLQR) & Differential Dynamic Programming (DDP)
    Iterative Linear Quadratic Regulator (iLQR) & Differential Dynamic Programming (DDP)
    
    iLQR
    iLQR
    
    iLQR
    
    iLQR Synthesis & Stabilization
    
    Convergent iLQR for Safe Trajectory Planning and Control of Legged Robots
    
    Differential Dynamic Programming
    Differential Dynamic Programming
    
    DDP
    
    Accelerating Second-Order Differential Dynamic Programming for Rigid-Body Systems
    
    300 years of optimal control: from the brachystochrone to the maximum principle
    
    Manipulator Inverse Kinematic Solutions Based on Vector Formulations and Damped Least-Squares Methods
    
    Optimal control of the double integrator with minimum total variation
    
    Relaxing Dynamic Programming
    
    Temporal Parallelization of Dynamic Programming and Linear Quadratic Control
    
    Time-optimal control of linear time invariant systems between two arbitrary states
    
    Differential dynamic programming and Newton's method for discrete optimal control problems
    
    Multiple Shooting DDP (MS-DDP)
    Multiple Shooting DDP (MS-DDP)
    
    iLQR-GNMS
    
    MS-DDP
    
    Unified Perspective on MS-DDP
    
    Convergence Guaranteed MS-DDP
    
    Tutorials & Convergence Theory
    Tutorials & Convergence Theory
    
    iLQR Algorithmic Templates
    
    Global & Local Convergence of iLQR/DDP
    
    Constrained DDP & iLQR
    Constrained DDP & iLQR
    
    Constrained LQR
    
    ALTRO
    
    AL-DDP
    
    FDDP
    
    Squash-Box FDDP
    
    AP-DDP
    
    FATROP
    
    Primal-Dual iLQR
    
    Primal-Dual iLQR (GPU)
    
    Crocoddyl
    
    CL-SQP
    
    ProxDDP
    
    Real-time Constrained Trajectory Optimization in Robotics: Theory, Implementation and Applications (Wilson Jallet PhD Dissertation)
    
    Second-Order Constrained DDP
    
    ALSPG
    
    GuSTO
    
    Elastic Smoothing
    Elastic Smoothing
    
    CES
    
    Nonlinear Optimization
    Nonlinear Optimization
    
    OBCA
    
    Differentiable Collision Avoidance Using Collision Primitives
    
    EGO-Planner
    
    TrajOpt
    
    Global Sampling-Based Trajectory Optimization for Contact-Rich Manipulation via KernelSOS
    
    ADMM-based Continuous Trajectory Optimization in Graphs of Convex Sets
    
    Dexterous contact-rich manipulation via the contact trust region
    
    Fast and Certifiable Trajectory Optimization
    
    Hippo
    
    Parallel-in-Time Nonlinear Optimal Control via GPU-native Sequential Convex Programming
    
    Using Reachable Sets for Trajectory Planning of Automated Vehicles
    
    KOMO
    
    A Sequential Operator-Splitting Framework for Exploration of Nonconvex Trajectory Optimization Solution Spaces
    
    Risk-Averse Trajectory Optimization via Sample Average Approximation
    
    Trajectory Optimization on Point Clouds
    Trajectory Optimization on Point Clouds
    
    Grasping Trajectory Optimization with Point Clouds
    
    Trajectory Optimization on Gaussian Splats
    Trajectory Optimization on Gaussian Splats
    
    SPLANNING
    
    FOCI
    
    Splat-Nav
    
    Hybrid Approaches
    Hybrid Approaches
    
    Sampled Differential Dynamic Programming (SaDDP)
    Sampled Differential Dynamic Programming (SaDDP)
    
    SaDDP
    
    Regularized SaDDP
    
    PI2-CMA
    
    PI2-DDP
    
    Grad+CEM
    
    MPPI-IPDDP
    
    DIAL-MPC
    
    Learning in Trajectory Optimization
    Learning in Trajectory Optimization
    
    MISO
    
    Probabilistic DDP
    
    DiffuSolve
    
    Accelerating trajectory optimization with Sobolev-trained diffusion policies
    
    Agile Autonomous Driving (End-to-End Imitation)
    
    DeepRacing
    
    Explaining How a Deep Neural Network Trained with End-to-End Learning Steers a Car
    
    Learning Complex Neural Network Policies with Trajectory Optimization
    
    Learning-Aided Warmstart of Model Predictive Control in Uncertain Fast-Changing Traffic
    
    Learning to Optimize in Model Predictive Control
    
    CACTO-BIC
    
    Improving Computational Efficiency for Powered Descent Guidance via Transformer-based Tight Constraint Prediction
    
    Deep Learning Warm Starts for Trajectory Optimization on the International Space Station
    
    Transformer-based Model Predictive Control: Trajectory Optimization via Sequence Modeling
    
    Hybrid Approaches
    Hybrid Approaches
    
    SBP-Guided MPC
    
    RRT-MPPI
    
    SETS
    
    Speed Planning
    Speed Planning
    
    Time-Optimal Path Parameterization (TOPP)
    Time-Optimal Path Parameterization (TOPP)
    
    TOPP
    
    AVP
    
    TOPP-RA
    
    Kinodynamic motion planning
    
    Optimization-based Speed Planning
    Optimization-based Speed Planning
    
    Path-Velocity Decomposition
    
    Time-Optimal Path Tracking for Robots: A Convex Optimization Approach
    
    Minimum-time Speed Optimisation Over a Fixed Path
    
    Toward a More Complete, Flexible, and Safer Speed Planning for Autonomous Driving via Convex Optimization
    
    Collision Avoidance
    Collision Avoidance
    
    Velocity Obstacles
    Velocity Obstacles
    
    Motion Planning in Dynamic Environments Using Velocity Obstacles
    
    ClearPath
    
    Reciprocal n-Body Collision Avoidance
    
    Reciprocal Velocity Obstacles for real-time multi-agent navigation
    
    Interaction-aware Planning
    Interaction-aware Planning
    
    Multimodal Probabilistic Model-Based Planning for Human-Robot Interaction
    
    VISTA 2.0
    
    Learning Interactive Driving Policies via Data-driven Simulation
    
    Tree-structured Policy Planning with Learned Behavior Models
    
    Causal Composition Diffusion Model for Closed-loop Traffic Generation
    
    Trajectory Tree-Based Pairwise Game for Interactive Decision-Making and Motion Planning in Autonomous Driving
    
    Machine Learning in Motion Planning
    Machine Learning in Motion Planning
    
    ALVINN
    
    Distance Metric Learning for RRT-Based Motion Planning with Constant-Time Inference
    
    RRT-CoLearn
    
    Neural RRT*
    
    Neural Informed RRT*
    
    SIL-RRT*
    
    Policy Optimization to Learn Adaptive Motion Primitives in Path Planning With Dynamic Obstacles
    
    MAB-RRT
    
    Train-Once Plan-Anywhere Kinodynamic Motion Planning via Diffusion Trees
    
    PRESTO
    
    DriveIRL
    
    Lab2Car
    
    Transitioning from Rule-Based to ML-Powered Motion Planning
    
    DiffusionSeeder: Seeding Motion Optimization with Diffusion for Rapid Motion Planning
    
    FlowDrive
    
    FlowMP
    
    Memory of Motion for Warm-starting Trajectory Optimization
    
    Parting with Misconceptions about Learning-based Vehicle Motion Planning
    
    Towards learning-based planning:The nuPlan benchmark for real-world autonomous driving
    
    Goal-Conditioned Neural ODEs with Guaranteed Safety and Stability for Learning-Based All-Pairs Motion Planning
    
    NuPlan
    
    GNN-DIP
    
    Inverse Kinematics
    Inverse Kinematics
    
    A combined optimization method for solving the inverse kinematics problems of mechanical manipulators
    
    Resolved Motion Rate Control of Manipulators and Human Prostheses
    
    JAX-IK
    
    Multi-Robot Planning
    Multi-Robot Planning
    
    Goal Assignment and Trajectory Planning
    
    Goal Assignment and Trajectory Planning for Large Teams of Aerial Robots
    
    CAPT
    
    Concurrent Goal Assignment and Collision-Free Trajectory Generation for Multiple Aerial Robots
    
    CanNoN-TaGS
    
    Trajectory Planning for Quadrotor Swarms
    
    CAT-ORA
    
    Agile and cooperative aerial manipulation of a cable-suspended load
    
    Safe multi-agent motion planning via filtered reinforcement learning
    
    Surveys & Comparative Studies
    Surveys & Comparative Studies
    
    An Empirical Study of Optimal Motion Planning
    
    A Survey of Motion Planning and Control Techniques for Self-Driving Urban Vehicles
    
    Connected and automated road vehicles: state of the art and future challenges
    
    Sampling-Based Methods for Motion Planning with Constraints
    
    Sampling-Based Motion Planning: A Comparative Review
    
    Planning and Decision-Making for Autonomous Vehicles
    
    Asymptotically Optimal Sampling-Based Motion Planning Methods
    
    Benchmarking Sampling-, Search-, and Optimization-based Approaches for Time-Optimal Kinodynamic Mobile Robot Motion Planning
    
    Motion Planning for Autonomous Driving: The State of the Art and Future Perspectives
    
    A Comparative Study of Rapidly-exploring Random Tree Algorithms Applied to Ship Trajectory Planning and Behavior Generation
    
    Motion Planning for Robotics: A Review for Sampling-based Planners
    
    DDP and MPPI on VTOL Aircraft
    
    A review of path following control strategies for autonomous robotic vehicles: theory, simulations, and experiments
    
    Contingency Planning for Safety-Critical Autonomous Vehicles: A Review and Perspectives
    
    Deeply Informed Neural Sampling for Robot Motion Planning
    
    Learning Sampling Distributions for Robot Motion Planning
    
    Motions in Microseconds via Vectorized Sampling-Based Planning
    
    On Infusing Reachability-Based Safety Assurance within Planning Frameworks for Human-Robot Vehicle Interactions
    
    Recent Developments in Aerial Robotics: A Survey and Prototypes Overview
    
    Results of the 2023 CommonRoad Motion Planning Competition for Autonomous Vehicles
    
    Scalable Autonomous Vehicle Safety Validation through Dynamic Programming and Scene Decomposition
    
    Score-Guided Motion Planning: Learning the Gradient Field of Promising Regions
    
    Frameworks & Stack Architectures
    Frameworks & Stack Architectures
    
    Rough Terrain Locomotion
    
    Boss
    
    A perception-driven autonomous urban vehicle
    
    RAKOMO
    
    An integrated system for real-time model predictive control of humanoid robots
    
    MJPC
    
    Judo
    
    Sumo
    
    Whole-Body Model-Predictive Control of Legged Robots with MuJoCo
    
    SONIC
    
    MPPI+IsaacGym
    
    DiffStack
    
    FRENETIX
    
    ROS
    
    ROS 2
    
    Motion Planning and Control for Multi Vehicle Autonomous Racing at High Speeds
  - Control
    Control
    
    Proportional-integral-derivative (PID)
    Proportional-integral-derivative (PID)
    
    A Practical Guide to PID Controller Implementation
    
    Linear Quadratic Regulator (LQR)
    Linear Quadratic Regulator (LQR)
    
    LQR Foundations
    LQR Foundations
    
    Suboptimal Design of Linear Regulator Systems
    
    Stabilization of Linear Systems
    
    On the linear quadratic minimum-time problem
    
    Riccati Equations
    Riccati Equations
    
    The Stabilizing Solution of the Algebraic Riccati Equation
    
    The Numerical Solution of A'Q+QA=-C
    
    On an Iterative Technique for Riccati Equation Computations
    
    An Iterative Technique for the Steady-State Gains
    
    A Numerical Algorithm to Solve A^T X A - X = Q
    
    Inexact Kleinman-Newton Method for Riccati Equations
    
    Solving the linear quadratic regulator problem in the policy space: The Policy Algebraic Riccati Equation
    
    Systematic Control Design by Optimizing a Vector Performance Index
    
    Multiplicative noise / stochastic system parameters
    Multiplicative noise / stochastic system parameters
    
    Experiments with an Inverted Pendulum Subject to Random Parametric Excitation
    
    A Survey of Stability of Stochastic Systems
    
    Optimal Stationary Control of a Linear System with State-Dependent Noise
    
    On the Separation Theorem of Stochastic Control
    
    Optimal Stationary Control of Linear Systems with Control-Dependent Noise
    
    The Optimal Regulator Problem for a Stationary Linear System with State-Dependent Noise
    
    Optimal Stationary Control with State and Control Dependent Noise
    
    Design of Linear Regulators for Nonlinear Stochastic Systems
    
    On Optimal Stationary Control of Systems with State-Dependent Noise
    
    The Uncertainty Threshold Principle: Fundamental Limitations
    
    Numerical Solution of the State-Dependent Noise Problem
    
    State-Feedback Control of Systems with Multiplicative Noise via LMIs
    
    When Multiplicative Noise Stymies Control
    
    Robust Control Design for Linear Systems via Multiplicative Noise
    
    Sample Complexity of Data-Driven Stochastic LQR with Multiplicative Uncertainty
    
    Data-driven distributionally robust LQR with multiplicative noise
    
    Stochastic Stability via Robustness of Linear Systems
    
    Stochasticity in Feedback Loops: Great Expectations and Guaranteed Ruin
    
    Anomaly Detection Under Multiplicative Noise Model Uncertainty
    
    Stochastic algebraic Riccati equations are almost as easy as deterministic ones theoretically
    
    Provably Stable Learning Control of Linear Dynamics With Multiplicative Noise
    
    Model Predictive Control (MPC)
    Model Predictive Control (MPC)
    
    Receding Horizon Control of Nonlinear Systems
    
    Robust model predictive control using tubes
    
    Data-driven distributionally robust MPC for constrained stochastic systems
    
    From linear to nonlinear MPC: bridging the gap via the real-time iteration
    
    Robust multi-rate predictive control using multi-step prediction models learned from data
    
    Learning multi-step prediction models for receding horizon control
    
    Learning with Imperfect Models: When Multi-step Prediction Mitigates Compounding Error
    
    On multi-step prediction models for receding horizon control
    
    Model predictive control of vehicle dynamics based on the Koopman operator with extended dynamic mode decomposition
    
    Data-Driven and Learning-Based MPC
    Data-Driven and Learning-Based MPC
    
    DeePC
    
    Model predictive control based on ARX models
    
    Learning-based predictive control for linear systems: a unitary approach
    
    KPC: Learning-Based Model Predictive Control with Deterministic Guarantees
    
    Exponential stability of data-driven nonlinear MPC based on input/output models
    
    Soft projections for robust data-driven control
    
    Stochastic Data-Driven Predictive Control: Regularization, Estimation, and Constraint Tightening
    
    Robust and Stochastic MPC
    Robust and Stochastic MPC
    
    Closed-loop analysis of linear stochastic MPC with risk-averse constraints
    
    Scenario-based Stochastic MPC for systems with uncertain dynamics
    
    MPC Applications and Implementations
    MPC Applications and Implementations
    
    Intelligent Trajectory Planning for Autonomous Vehicles via Adaptive Model Predictive Control
    
    Robust Nonlinear Trajectory Tracking Control for Autonomous Racing on Three-Dimensional Tracks
    
    Robust Control
    Robust Control
    
    Linear Matrix Inequalities in System and Control Theory
    
    LMI Properties and Applications in Systems, Stability, and Control Theory
    
    Robustness margins for LQG
    
    DR-LQG
    
    Conformal Robust Control of Linear Systems
    
    Probabilistic Robustness in the Gap Metric
    
    On the Input-Output Stability of Time-Varying Nonlinear Feedback Systems
    
    State-Space Solutions to Standard H2 and H-inf Control Problems
    
    LQG Control with an H-infinity Performance Bound: A Riccati Equation Approach
    
    On the Robustness of LQ Regulators for Discrete-Time Systems
    
    A Method to Teach the Parameterization of All Stabilizing Controllers
    
    Policy Optimization of Mixed H2/H-infinity Control: Benign Nonconvexity and Global Optimality
    
    System analysis via integral quadratic constraints
    
    Perception-Based Control
    Perception-Based Control
    
    Robust Guarantees for Perception-Based Control
    
    Certainty Equivalent Perception-Based Control
    
    Control Co-Design
    Control Co-Design
    
    Gradient-Based Plant-Controller Co-Design
    
    Control-Oriented Physical Modeling
    Control-Oriented Physical Modeling
    
    5-DOF Electrodynamic Maglev State-Space Model
    
    Control-Oriented Modeling of the Dynamics of Stirling Engine Regenerators
    
    Control Theory
    Control Theory
    
    The Internal Model Principle for Linear Multivariable Regulators
    
    Every Good Regulator Theorem
    
    Internal feedback in the cortical perception-action loop enables fast and accurate behavior
    
    Path-Following or Reference-Tracking
    
    DWPP
    
    Control Principles of Complex Networks
    
    Control Profiles of Complex Networks
    
    Control for Societal-Scale Challenges
    
    A note on persistency of excitation
    
    Respect the unstable
    
    Augmented Lagrangian Methods as Layered Control Architectures
    
    Towards a Theory of Control Architecture: A quantitative framework for layered multi-rate control
    
    Asymptotic stability equals exponential stability - while you twist your eyes
    
    Control Lyapunov Functions
    Control Lyapunov Functions
    
    Stabilization with Relaxed Controls
    
    A Lyapunov-Like Characterization of Asymptotic Controllability
    
    Sontag's Universal Formula
    
    A 'universal' construction of Artstein's theorem on nonlinear stabilization
    
    Control Barrier Functions (CBF) and Control Lyapunov Functions (CLF)
    Control Barrier Functions (CBF) and Control Lyapunov Functions (CLF)
    
    Co-designing Control Barrier Functions and Linear State-Feedback Controllers
    
    Convex synthesis and verification of control-Lyapunov and barrier functions with input constraints
    
    A Barrier-Based Scenario Approach to Verifying Safety-Critical Systems
    
    Control Barrier Function Based Quadratic Programs for Safety Critical Systems
    
    Control Barrier Functions: Theory and Applications
    
    Synthesis and Deployment of Maximal Robust Control Barrier Functions through Adversarial Reinforcement Learning
    
    Vehicle Dynamics
    Vehicle Dynamics
    
    The Tire-Force Ellipse
    
    Kinematic modeling of wheeled mobile robots
    
    On the Kinematics of Wheeled Mobile Robots
    
    The Magic Formula Tyre Model
    
    Structural properties and classification of kinematic and dynamic models of wheeled mobile robots
    
    Kinematic and dynamic vehicle models for autonomous driving control design
    
    Underactuated Systems
    Underactuated Systems
    
    Acrobot
    
    CartPole (Correct Equations)
    
    BOBShield
    
    A Data-Driven Approach to Synthesizing Dynamics-Aware Trajectories for Underactuated Robotic Systems
  - Reinforcement Learning
    Reinforcement Learning
    
    Foundations
    Foundations
    
    Neuronlike Adaptive Elements (Actor-Critic, Cart-Pole)
    
    TD Learning
    
    mellowmax
    
    A Gentle Lecture Note on Filtrations in Reinforcement Learning
    
    Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review
    
    Imitation Learning
    Imitation Learning
    
    DAgger
    
    Efficient Reductions for Imitation Learning
    
    TaSIL
    
    Grasping with Chopsticks
    
    DROID
    
    HRT1
    
    Is Behavior Cloning All You Need?
    
    Pitfalls of Imitation Learning
    
    Action Chunking and Exploratory Data Collection Yield Exponential Improvements in Behavior Cloning for Continuous Control
    
    A Careful Examination of Large Behavior Models for Multitask Dexterous Manipulation
    
    Sample-Efficient Expert Query Control in Active Imitation Learning via Conformal Prediction
    
    Multi-arm Bandits
    Multi-arm Bandits
    
    Finite-time Analysis of the Multiarmed Bandit Problem
    
    RL for Linear Systems
    RL for Linear Systems
    
    Data-driven Control and Planning for Uncertain Complex Systems (Gravell PhD Dissertation)
    
    Policy Optimization
    Policy Optimization
    
    Global Convergence of Policy Gradient Methods for LQR
    
    Learning Robust Control for LQR Systems with Multiplicative Noise via Policy Gradient
    
    Sparse Optimal Control of Networks with Multiplicative Noise via Policy Gradient
    
    Policy Gradient Converges to the Globally Optimal Policy for Nearly Linear-Quadratic Regulators
    
    LQR through the Lens of First Order Methods
    
    Policy Optimization Provably Converges to Nash Equilibria in Zero-Sum LQ Games
    
    Convergence of Flow-Policy Gradient Learning for Linear Quadratic Regulator Problems
    
    On the Optimization Landscape of Observer-based Dynamic Linear Quadratic Control
    
    Policy Gradient for LQR with Domain Randomization
    
    Second-Order Policy Gradient Methods for the Linear Quadratic Regulator
    
    Model-Agnostic Meta-Policy Optimization via Zeroth-Order Estimation: A Linear Quadratic Regulator Perspective
    
    Scalar Federated Learning for Linear Quadratic Regulator
    
    Dynamic Programming
    Dynamic Programming
    
    Policy iteration using Q-functions: Linear dynamics with multiplicative noise
    
    Policy Iteration for Linear Quadratic Games with Stochastic Parameters
    
    Model-based RL
    Model-based RL
    
    Logarithmic Regret for Online Control
    
    Regret Bounds for the Adaptive Control of Linear Quadratic Systems
    
    Regret Bounds for Robust Adaptive Control of LQR
    
    Regret Bounds for Robust Adaptive Control of the Linear Quadratic Regulator
    
    Certainty Equivalence is Efficient for Linear Quadratic Control
    
    Domain Randomization is Sample Efficient for Linear Quadratic Control
    
    Robust Learning-Based Control via Bootstrapped Multiplicative Noise
    
    Robust Data-Driven Output Feedback Control via Bootstrapped Multiplicative Noise
    
    Efficient Learning of a Linear Dynamical System with Stability Guarantees
    
    CLT-Optimal Parameter Error Bounds for Linear System Identification
    
    Dynamic Programming
    Dynamic Programming
    
    Exact Dynamic Programming
    Exact Dynamic Programming
    
    On the Convergence of Policy Iteration in Stationary Dynamic Programming
    
    Values and Strategies for Infinite Time Linear Quadratic Games
    
    Quasi Policy Iteration
    
    Dynamic Programming Through the Lens of Semismooth Newton-Type Methods
    
    Approximate Dynamic Programming
    Approximate Dynamic Programming
    
    On-Line Q-Learning Using Connectionist Systems
    
    Adaptive Linear Quadratic Control Using Policy Iteration
    
    LSPI
    
    Approximate Dynamic Programming via Sum of Squares Programming
    
    Finite-Time Analysis of Approximate Policy Iteration for LQR
    
    AMPI
    
    Value-Gradient Iteration with Quadratic Approximate Value Functions
    
    Deep Value-Based
    Deep Value-Based
    
    DQN (Playing Atari with Deep RL)
    
    Prioritized Experience Replay
    
    Double DQN
    
    Dueling Networks
    
    Rainbow
    
    Policy Optimization
    Policy Optimization
    
    Random Search & Evolution Strategies
    Random Search & Evolution Strategies
    
    ARS
    
    Derivative-Free Methods for Policy Optimization
    
    NEAT
    
    Embodied Intelligence via Learning and Evolution
    
    Policy Gradient
    Policy Gradient
    
    REINFORCE
    
    Policy Gradient Methods for Reinforcement Learning with Function Approximation
    
    Natural Policy Gradient
    
    HOOF
    
    Evolution Strategies as a Scalable Alternative to Reinforcement Learning
    
    How are policy gradient methods affected by the limits of control?
    
    On Linear Convergence of Policy Gradient Methods for Finite MDPs
    
    On the Theory of Policy Gradient Methods: Optimality, Approximation, and Distribution Shift
    
    On-Policy Distillation of Language Models for Autonomous Vehicle Motion Planning
    
    PAGE-PG
    
    Stochastic Variance-Reduced Policy Gradient
    
    The Definitive Guide to Policy Gradients in Deep Reinforcement Learning: Theory, Algorithms and Implementations
    
    Understanding the Effects of Second-Order Approximations in Natural Policy Gradient Reinforcement Learning
    
    Do Differentiable Simulators Give Better Policy Gradients?
    
    A Large Deviations Perspective on Policy Gradient Algorithms
    
    Stochastic Recursive Momentum for Policy Gradient Methods
    
    Actor-Critic Methods
    Actor-Critic Methods
    
    DPG
    
    DDPG
    
    A3C
    
    GAE
    
    ACKTR
    
    TD3
    
    SAC
    
    ACER
    
    Q-Prop
    
    Emergence of Locomotion Behaviours in Rich Environments
    
    FlashSAC
    
    Trust Region
    Trust Region
    
    TRPO
    
    PPO
    
    QNTRPO
    
    SPO
    
    GRPO
    
    KIPPO
    
    Bounded Ratio Reinforcement Learning
    
    Model-Based RL
    Model-Based RL
    
    Surveys & Control Connections
    Surveys & Control Connections
    
    From Self-Tuning Regulators to Reinforcement Learning and Back Again
    
    A Tour of Reinforcement Learning: The View from Continuous Control
    
    A view on learning robust goal-conditioned value functions: Interplay between RL and MPC
    
    Synthesis of Model Predictive Control and Reinforcement Learning: Survey and Classification
    
    MPC-RL Hybrids
    MPC-RL Hybrids
    
    Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control
    
    Information Theoretic Model Predictive Q-Learning
    
    Differentiable MPC for End-to-end Planning and Control
    
    Actor-Critic Model Predictive Control: Differentiable Optimization meets Reinforcement Learning for Agile Flight
    
    MPCritic
    
    Policy Optimization for Unknown Systems using Differentiable Model Predictive Control
    
    Soft MPCritic: Amortized Model Predictive Value Iteration
    
    Temporal Difference Learning for Model Predictive Control
    
    TD-MPC2
    
    System Identification
    System Identification
    
    Non-Asymptotic Identification of LTI Systems from a Single Trajectory
    
    Finite Sample Analysis of Stochastic System Identification
    
    A Tutorial on Concentration Bounds for System Identification
    
    Linear System Identification Under Multiplicative Noise from Multiple Trajectory Data
    
    Identification of Linear Systems with Multiplicative Noise from Multiple Trajectory Data
    
    Subspace Identification
    Subspace Identification
    
    Subspace Identification for Linear Systems
    
    N4SID
    
    ERA
    
    OKID
    
    Dynamic Mode Decomposition (DMD)
    Dynamic Mode Decomposition (DMD)
    
    DMD
    
    DMD: Theory and Applications
    
    DMD: Theory and Data Reconstruction
    
    DMD and Its Variants
    
    DMDc
    
    eDMD
    
    A Short Introduction to the Koopman Representation of Dynamical Systems
    
    Accelerating Sampling-Based Control via Learned Linear Koopman Dynamics
    
    Data-driven discovery of Koopman eigenfunctions for control
    
    Data-Driven Feedback Linearization using the Koopman Generator
    
    Interpreting Reinforcement Learning Model Behavior via Koopman with Control
    
    Sparse Identification of Nonlinear Dynamics (SINDy)
    Sparse Identification of Nonlinear Dynamics (SINDy)
    
    SINDy
    
    SINDy with Control
    
    SINDy-MPC
    
    SINDy-RL
    
    PySINDy
    
    LeARN
    
    World Models
    World Models
    
    PlaNet
    
    Dreamer
    
    Dream to Fly
    
    Hierarchical Planning with Latent World Models
    
    A Tutorial on Solution Properties of State Space Models of Dynamical Systems
    
    An Information-state based Approach to the Optimal Output Feedback Control of Nonlinear Systems
    
    An Introduction to Matrix Concentration Inequalities
    
    Concentration Inequalities for Statistical Inference
    
    How Are Learned Perception-Based Controllers Impacted by the Limits of Robust Control?
    
    Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems
    
    Self-Normalized Processes: Exponential Inequalities, Moment Bounds and Iterated Logarithm Laws
    
    State space models vs. multi-step predictors in predictive control: Are state space models complicating safe data-driven designs?
    
    Statistical Efficiency of Single- and Multi-step Models for Forecasting and Control
    
    System identification and long-range predictive control of multi-rate systems
    
    Hybrid Approaches
    Hybrid Approaches
    
    Model-Based Value Estimation for Efficient Model-Free Reinforcement Learning
    
    PLAL
    
    Power of Locally Linear Models
    
    Diffusion & Flow Matching
    Diffusion & Flow Matching
    
    Diffusion Policy
    
    Planning with Diffusion for Flexible Behavior Synthesis
    
    Tree-Guided Diffusion Planner
    
    Streaming Flow Policy
    
    OGPO
    
    From Demonstrations to Safe Deployment: Path-Consistent Safety Filtering for Diffusion Policies
    
    Much Ado About Noising: Dispelling the Myths of Generative Robotic Control
    
    Inverse Reinforcement Learning & Reward Learning
    Inverse Reinforcement Learning & Reward Learning
    
    Inverse Optimization: Theory and Applications
    
    Inverse LQR
    
    Efficient Reward Identification in Max Entropy Reinforcement Learning with Sparsity and Rank Priors
    
    Applications of RL
    Applications of RL
    
    Learning Dexterous In-Hand Manipulation
    
    Outracing champion Gran Turismo drivers with deep reinforcement learning
    
    Spatial planning of urban communities via deep reinforcement learning
- Prediction
  Prediction
  - Motion Prediction
    Motion Prediction
    
    Traffic Models
    Traffic Models
    
    IDM
    
    An adaptive lateral preview driver model
    
    Human-like driving behaviour emerges from a risk-based driver model
    
    Multi-agent & Interaction-aware Prediction
    Multi-agent & Interaction-aware Prediction
    
    Trajectron++
    
    Wayformer
    
    VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representation
    
    Prediction Horizon
    Prediction Horizon
    
    Prediction Horizon Requirements for Automated Driving
    
    Accelerated Evaluation of Automated Vehicles Safety in Lane Change Scenarios Based on Importance Sampling Techniques
    
    Surveys
    Surveys
    
    Trends in Motion Prediction Toward Deployable and Generalizable Autonomy
    
    Motion Forecasting for Autonomous Vehicles
    
    Trajectory Prediction for Autonomous Driving
    
    Deep Learning-based Vehicle Behaviour Prediction
    
    A Survey on Motion Prediction and Risk Assessment for Intelligent Vehicles
    
    Action and Trajectory Prediction for Autonomous Driving
    
    A survey on motion prediction and risk assessment for intelligent vehicles
    
    DriveGPT: Scaling Autoregressive Behavior Models for Driving
    
    Forecasting the Past: Gradient-Based Distribution Shift Detection in Trajectory Prediction
    
    Task-Relevant Failure Detection for Trajectory Predictors in Autonomous Vehicles
    
    Time-aware Motion Planning in Dynamic Environments with Conformal Prediction
    
    WestWorld: A Knowledge-Encoded Scalable Trajectory World Model for Diverse Robotic Systems
    
    Real-Time Learning of Predictive Dynamic Obstacle Models for Robotic Motion Planning
  - State Estimation
    State Estimation
    
    Kalman Filter
    Kalman Filter
    
    Kalman Filter
    
    Optimal Adaptive Estimation of Sampled Stochastic Processes
    
    Adaptive Kalman filter
    
    Fitting a Kalman Smoother to Data
    
    Wasserstein Distributionally Robust Kalman Filtering
    
    Unscented Kalman Filter (UKF)
    Unscented Kalman Filter (UKF)
    
    UKF
    
    The Unscented Kalman Filter for Nonlinear Estimation
    
    The Scaled Unscented Transformation
    
    Particle Filters
    Particle Filters
    
    CONDENSATION
    
    Particle filters for positioning, navigation, and tracking
    
    Marginalized particle filters for mixed linear/nonlinear state-space models
    
    Mapping & SLAM
    Mapping & SLAM
    
    Hydra
    
    Khronos
    
    OctoMap
    
    Fast Iterative Alignment of Pose Graphs with Poor Initial Estimates
    
    Factor Graphs: Exploiting Structure in Robotics
    
    Building Rome with Convex Optimization
    
    Learning Occupancy Grid Maps with Forward Sensor Models
  - Machine Learning
    Machine Learning
    
    Foundations
    Foundations
    
    From Entropy to Epiplexity: Rethinking Information for Computationally Bounded Intelligence
    
    Uncertainty Quantification
    Uncertainty Quantification
    
    Backward Conformal Prediction
    
    Datasets
    Datasets
    
    MNIST
    
    The Lost MNIST Digits
    
    MNIST-1D
    
    Interpretability
    Interpretability
    
    Shapley
    Shapley
    
    Shapley Value
    
    SHAP
    
    TreeSHAP
    
    "Why Should I Trust You?": Explaining the Predictions of Any Classifier
    
    Beyond Sparsity: Tree Regularization of Deep Models for Interpretability
    
    Explainable AI: Learning from the Learners
    
    Explainable deep learning improves human mental models of self-driving cars
    
    Grad-CAM
    
    Intelligible Models for HealthCare
    
    Interpretable machine learning: definitions, methods, and applications
    
    InterpretML
    
    SLIM
    
    Opportunities and Challenges in Explainable Artificial Intelligence (XAI): A Survey
    
    Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead
    
    The Mythos of Model Interpretability
    
    Towards A Rigorous Science of Interpretable Machine Learning
    
    Clustering
    Clustering
    
    k-means
    k-means
    
    k-means
    
    Least squares quantization in PCM
    
    k-means++
    
    Hierarchical Clustering
    Hierarchical Clustering
    
    Ward's Method
    
    Density-based Clustering
    Density-based Clustering
    
    OPTICS
    
    DBSCAN
    
    HDBSCAN
    
    Accelerated HDBSCAN
    
    DenMune
    
    Spectral Clustering
    Spectral Clustering
    
    Spectral Clustering
    
    Deep Embedding Clustering
    Deep Embedding Clustering
    
    DEC
    
    DEPICT
    
    N2D
    
    Dimensionality Reduction
    Dimensionality Reduction
    
    DrLIM
    
    t-SNE
    
    Accelerating t-SNE using Tree-Based Algorithms
    
    UMAP
    
    Understanding How Dimension Reduction Tools Work: An Empirical Approach to Deciphering t-SNE, UMAP, TriMAP, and PaCMAP for Data Visualization
    
    Decision Trees
    Decision Trees
    
    AID
    
    CHAID
    
    CART
    
    ID3
    
    C4.5
    
    ctree
    
    Kernel Machines
    Kernel Machines
    
    SVM
    
    Random Kitchen Sinks
    
    A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting
    
    Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees
    
    Every Model Learned by Gradient Descent Is Approximately a Kernel Machine
    
    Ensemble Methods
    Ensemble Methods
    
    Bagging
    
    Random Forests
    
    GBM
    
    XGBoost
    
    LightGBM
    
    CatBoost
    
    Finding Influential Training Samples for Gradient Boosted Decision Trees
    
    Gradient Boosting Performs Gaussian Process Inference
    
    Neural Networks
    Neural Networks
    
    Perceptron
    
    Backpropagation
    
    Siamese Neural Network
    
    Gradient-Based Learning Applied to Document Recognition
    
    LSTM
    
    U-Net
    
    ELU
    
    Dropout
    
    Understanding deep learning requires rethinking generalization
    
    Reconciling modern machine learning practice and the bias-variance trade-off
    
    Deep Double Descent: Where Bigger Models and More Data Hurt
    
    Do CIFAR-10 Classifiers Generalize to CIFAR-10?
    
    Grokking
    
    Vision-language-action (VLA) Models
    Vision-language-action (VLA) Models
    
    GR00T N1
    
    Alpamayo-R1
    
    Orion-Lite
    
    MolmoAct2
    
    RLDX-1
    
    Natural Language Processing (NLP)
    Natural Language Processing (NLP)
    
    BERTopic
    
    Large language models (LLM)
    Large language models (LLM)
    
    Llama 2
    
    LoRA
    
    AnglE
    
    Meta-Harness
    
    Transformers & Attention-based models
    Transformers & Attention-based models
    
    Attention Is All You Need
    
    FlashAttention
    
    Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
    
    Reducing the Transformer Architecture to a Minimum
    
    Diffusion Models
    Diffusion Models
    
    Denoising Diffusion Probabilistic Models
    
    ChopGrad
    
    Deblurring via Stochastic Refinement
    
    Is Your Conditional Diffusion Model Actually Denoising?
    
    State-space Models (SSM)
    State-space Models (SSM)
    
    Spectral State Space Models
    
    Multimodal Models
    Multimodal Models
    
    Zero-Shot Text-to-Image Generation
    
    Learning Transferable Visual Models From Natural Language Supervision
    
    Hierarchical Text-Conditional Image Generation with CLIP Latents
    
    Generative Models
    Generative Models
    
    Auto-Encoding Variational Bayes
    
    Generative Adversarial Networks
    
    Image Generators are Generalist Vision Learners
    
    Representation Learning
    Representation Learning
    
    A Topology Layer for Machine Learning
    
    Distance Metric Learning for Large Margin Nearest Neighbor Classification
    
    A Cookbook of Self-Supervised Learning
    
    BYOL
    
    Barlow Twins
    
    VICReg
    
    Energy-based Models
    
    Time Series
    Time Series
    
    Algorithms
    Algorithms
    
    BOSS
    
    DTW
    
    Exact indexing of dynamic time warping
    
    Gated Transformer Networks for Multivariate Time Series Classification
    
    Forecasting at Scale
    
    HierarchicalForecast
    
    Time series shapelets
    
    Informer
    
    InceptionTime
    
    ROCKET
    
    MINIROCKET
    
    MultiRocket
    
    QUANT
    
    TimeGPT-1
    
    Surveys and Comparative Studies
    Surveys and Comparative Studies
    
    Bake Off Redux
    
    Time series classification: nearest neighbor versus deep learning models
    
    Time Series Embedding Methods for Classification Tasks: A Review
    
    Transformers in Time Series: A Survey
    
    Explainability
    Explainability
    
    Higher-order organization of multivariate time series
    
    Understanding Any Time Series Classifier with a Subsequence-based Explainer
  - Computer Vision
    Computer Vision
    
    Edge Detection
    Edge Detection
    
    Sobel Operator
    
    Theory of Edge Detection
    
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