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Optimization
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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
A Computational Approach to Edge Detection
Object Detection
Object Detection
A General Framework for Object Detection
Viola-Jones Detector
HOG
YOLO
3D Vision & Shape Understanding
3D Vision & Shape Understanding
3D ShapeNets
ShapeNet
Face Recognition
Face Recognition
FaceNet
Feature Detection & Description
Feature Detection & Description
SIFT
SURF
Image Classification & Recognition
Image Classification & Recognition
Inception/GoogLeNet
VGG
ResNet
ViT
Swin Transformer
DINO
DINOv2
DINOv3
Image Quality Assessment
Image Quality Assessment
SSIM
Understanding SSIM
A new Image Similarity Metric for a Perceptual and Transparent Geometric and Chromatic Assessment
Color & Perception
Color & Perception
Visual Sensitivities to Color Differences in Daylight
IPT Color Space
Uniform colour spaces based on CIECAM02 colour appearance model
Image Processing & Computational Photography
Image Processing & Computational Photography
End-to-end Optimized Image Compression
Lossy Image Compression with Compressive Autoencoders
Polyblur
Burst photography for high dynamic range and low-light imaging on mobile cameras
Nano Banana Pro
What Matters in Practical Learned Image Compression
Video Understanding
Video Understanding
ViViT
V-JEPA
V-JEPA 2
Evaluation
Evaluation
Simulation
Simulation
CARLA
GPUDrive
KinDER
MuJoCo Playground
Orbit
NAVSIM
NAVSIM v2
RoboPlayground
Waymo Open Sim Agents Challenge
Waymax
Benchmarks
Benchmarks
Gym
Isaac Gym
controlgym
Safety, Testing & Verification
Safety, Testing & Verification
A Simple and Efficient Sampling-based Algorithm for General Reachability Analysis
How Should a Robot Assess Risk?
Formal Specification for Deep Neural Networks
Challenges in Autonomous Vehicle Testing and Validation
Driving to Safety: How Many Miles of Driving Would It Take to Demonstrate Autonomous Vehicle Reliability?
The MIT-Cornell collision and why it happened
Methodology for determining maximum injury potential for automated driving system evaluation
Risk-Aware Robotics: Tail Risk Measures in Planning, Control, and Verification
Unconventional Roundabouts: Third-Generation Insights from the United States and Europe
Safety Evaluation of Motion Plans Using Trajectory Predictors as Forward Reachable Set Estimators
IEEE Standard 3079-2022
A new accident model for engineering safer systems
Assume/Guarantee Contracts for Dynamical Systems: Theory and Computational Tools
Learning Autonomous Vehicle Safety Concepts from Demonstrations
On a Formal Model of Safe and Scalable Self-driving Cars
The Field of Safe Motion: Operationalizing Affordances in the Field of Safe Travel Using Reachability Analysis
On the validation of complex systems operating in open contexts
Testing, Validation, and Verification of Robotic and Autonomous Systems: A Systematic Review
Computing
Computing
Network Science
Network Science
Centrality
Centrality
PageRank
Community Detection
Community Detection
Louvain Algorithm
Leiden Algorithm
Algorithms & Data Structures
Algorithms & Data Structures
Probabilistic Data Structures
Probabilistic Data Structures
Space/time trade-offs in hash coding with allowable errors
HyperLogLog
Cuckoo Filter
Nearest Neighbor Search
Nearest Neighbor Search
FLANN
Accelerating Large-Scale Inference with Anisotropic Vector Quantization
Billion-scale similarity search with GPUs
CLOVER
Efficient and robust approximate nearest neighbor search using Hierarchical Navigable Small World graphs
JZ-Tree
Neural Nearest Neighbors Networks
Product Quantization for Nearest Neighbor Search
FAISS
Complexity & Approximation
Complexity & Approximation
Randomized greedy algorithms for covering problems
Reducibility among Combinatorial Problems
Parallel Algorithms
Parallel Algorithms
Fast parallel matrix inversion algorithms
Scans as primitive parallel operations
Priority Queues
Priority Queues
Fibonacci Heap
Sorting
Sorting
Quicksort
Heapsort
Introsort
Pattern-defeating Quicksort
Trees & Spatial Indexing
Trees & Spatial Indexing
A dichromatic framework for balanced trees
Multidimensional binary search trees used for associative searching
Organization and maintenance of large ordered indices
Quad Trees
SR-tree
STAR-Tree
Ubiquitous B-Tree
R-trees
Software & Programming
Software & Programming
The Humble Programmer
On the Role of Scientific Thought
Scientific Computing & ML Systems
Scientific Computing & ML Systems
JAX
frax
DuckDB
Matplotlib
PyTorch
Ray
RLlib
Tune
Art & Practice
C++
Python
Interoperability
Trajectory Optimization
Computer Graphics
Computer Graphics
Subdivision Surfaces
Subdivision Surfaces
Catmull-Clark Subdivision Surfaces
Geometry Processing
Geometry Processing
Marching Cubes
Animation & Simulation
Animation & Simulation
Boids
Noise & Dithering
Noise & Dithering
Perlin Noise
Blue Noise Dithering
Forced Random Dithering
Scalar Spatiotemporal Blue Noise Masks
Flow Visualization
Flow Visualization
OLIC
3D Gaussian Splatting
3D Gaussian Splatting
3D Gaussian Splatting
Matrix-free Second-order Optimization of Gaussian Splats with Residual Sampling
Neural Rendering
Neural Rendering
NeRF
Misc
Misc
Mathematics
Mathematics
Geometry & Tiling
Geometry & Tiling
An aperiodic monotile
A chiral aperiodic monotile
A Simple Proof of Thue's Theorem on Circle Packing
The Table Theorem
Topology
Topology
Dyson's Sphere Theorem
Linear Algebra & Signal Processing
Linear Algebra & Signal Processing
Cooley-Tukey FFT
Discovering Transforms: A Tutorial on Circulant Matrices, Circular Convolution, and the Discrete Fourier Transform
Numerical Methods
Numerical Methods
A family of embedded Runge-Kutta formulae
Sampling & Quasi-Monte Carlo
Sampling & Quasi-Monte Carlo
Neural Low-Discrepancy Sequences
Statistics & Probability
Statistics & Probability
Mean, What do You Mean?
Optimal Inequalities in Probability Theory: A Convex Optimization Approach
History
History
Thomas Simpson and 'Newton's Method of Approximation': An Enduring Myth
The Stirling Engine of 1816
Review of Computational Stirling Analysis Methods
How the oldest recorded multiple facility location problem was solved
Technological challenges and optimization efforts of the Stirling machine: A review
Just for Fun
Just for Fun
Evolving Virtual Creatues
Evolving Virtual Creatues
Evolving Virtual Creatures
Unshackling Evolution
Robot Platforms
Robot Platforms
Duckietown
ANYmal
Cheetah 3
Mini Cheetah
Design and Control of a Bipedal Robotic Character
Explainers
Explainers
Planning & Control
Planning & Control
PID
LQR
MPC
MCTS
Differential Flatness
AkinoPDF
Respect the Unstable
Explorations in Dynamics
Permutation-Invariant Neural Nets for RL
Optimization
Optimization
Gradient Descent under Polyak-Łojasiewicz
AI for Autonomy
AI for Autonomy
Waymo AI
Adversarial Training and Robot Safety
Analytics
Portfolio
Programming: Art & Practice
¶
What is Premature Abstraction?
PEP 20 – The Zen of Python