← Authors

Byron Boots

83 papers · 2007–2025 · 12 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (18) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (13) 🌍 Conference Polyglot (12) πŸ—ΊοΈ Taxonomy Completionist (19) 🏠 Conference Loyalist (23) 🀝 Dynamic Duo (19) πŸ† Keyword Champion (3) πŸ”¬ Deep Specialist (12) 🧬 Topic Evolution πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ”₯ Unstoppable (11) ⚑ Prolific Year (10) πŸ’Ž Century Club (83) πŸ—ƒοΈ Keyword Collector (57)

Conferences

CORL (23) NIPS (12) AISTATS (11) RSS (11) ICML (9) ICLR (5) ICCV (4) L4DC (3) IJCAI (2) ECCV (1) UAI (1) WACV (1)

Top co-authors

Ching-An Cheng (19) Dieter Fox (11) Amirreza Shaban (9) Mustafa Mukadam (8) Wen Sun (7) Anqi Li (7) Geoffrey J. Gordon (6) Xinyan Yan (6) Mohak Bhardwaj (6) Xiangyun Meng (6)

Research topics

Reinforcement Learning (1)

Keywords

imitation learning (10) reinforcement learning (9) model predictive control (9) motion planning (7) policy learning (5) policy optimization (5) variational inference (4) online learning (4) predictive state representation (4) gaussian process (4) hidden markov model (3) semantic segmentation (3) stochastic process (3) dynamical system (3) bayesian inference (3) system identification (3) markov decision process (3) probabilistic inference (3) optimal control (3) model-based reinforcement learning (3)

Papers

Uncertainty-aware Accurate Elevation Modeling for Off-road Navigation via Neural Processes CORL 2025
Long Range Navigator (LRN): Extending robot planning horizons beyond metric maps CORL 2025
Details Matter for Indoor Open-vocabulary 3D Instance Segmentation ICCV 2025
Tactile Beyond Pixels: Multisensory Touch Representations for Robot Manipulation CORL 2025
Wheeled Lab: Modern Sim2Real for Low-cost, Open-source Wheeled Robotics CORL 2025
Self-supervised perception for tactile skin covered dexterous hands CORL 2025
Sparsh: Self-supervised touch representations for vision-based tactile sensing CORL 2024
BeigeMaps: Behavioral Eigenmaps for Reinforcement Learning from Images ICML 2024
Model Predictive Control for Aggressive Driving Over Uneven Terrain RSS 2024
Avoid Everything: Model-Free Collision Avoidance with Expert-Guided Fine-Tuning CORL 2024
TerrainNet: Visual Modeling of Complex Terrain for High-speed, Off-road Navigation RSS 2023
CAFA: Class-Aware Feature Alignment for Test-Time Adaptation ICCV 2023
DATT: Deep Adaptive Trajectory Tracking for Quadrotor Control CORL 2023
MAHALO: Unifying Offline Reinforcement Learning and Imitation Learning from Observations ICML 2023
Adversarial Model for Offline Reinforcement Learning NIPS 2023
Continuous Versatile Jumping Using Learned Action Residuals L4DC 2023
DYNAMO-GRASP: DYNAMics-aware Optimization for GRASP Point Detection in Suction Grippers CORL 2023
CAJun: Continuous Adaptive Jumping using a Learned Centroidal Controller CORL 2023
LiDAR-UDA: Self-ensembling Through Time for Unsupervised LiDAR Domain Adaptation ICCV 2023
Motion Policy Networks CORL 2022
Learning Semantics-Aware Locomotion Skills from Human Demonstration CORL 2022
Few-Shot Weakly-Supervised Object Detection via Directional Statistics WACV 2022
Learning Sampling Distributions for Model Predictive Control CORL 2022
RMP2: A Structured Composable Policy Class for Robot Learning RSS 2021
Safe Reinforcement Learning Using Advantage-Based Intervention ICML 2021
Blending MPC & Value Function Approximation for Efficient Reinforcement Learning ICLR 2021
Explaining fast improvement in online imitation learning UAI 2021
Semantic Terrain Classification for Off-Road Autonomous Driving CORL 2021
STORM: An Integrated Framework for Fast Joint-Space Model-Predictive Control for Reactive Manipulation CORL 2021
Fast and Efficient Locomotion via Learned Gait Transitions CORL 2021
Motivating Physical Activity via Competitive Human-Robot Interaction CORL 2021
Quantum Tensor Networks, Stochastic Processes, and Weighted Automata AISTATS 2021
Dual Online Stein Variational Inference for Control and Dynamics RSS 2021
Intra Order-preserving Functions for Calibration of Multi-Class Neural Networks NIPS 2020
Learning a Contact-Adaptive Controller for Robust, Efficient Legged Locomotion CORL 2020
Stein Variational Model Predictive Control CORL 2020
Online Learning with Continuous Variations: Dynamic Regret and Reductions AISTATS 2020
A Reduction from Reinforcement Learning to No-Regret Online Learning AISTATS 2020
Expressiveness and Learning of Hidden Quantum Markov Models AISTATS 2020
Pairwise Similarity Knowledge Transfer for Weakly Supervised Object Localization ECCV 2020
Composing Task-Agnostic Policies with Deep Reinforcement Learning ICLR 2020
Euclideanizing Flows: Diffeomorphic Reduction for Learning Stable Dynamical Systems L4DC 2020
Information Theoretic Model Predictive Q-Learning L4DC 2020
An Online Learning Approach to Model Predictive Control RSS 2019
Provably Efficient Imitation Learning from Observation Alone ICML 2019
Predictor-Corrector Policy Optimization ICML 2019
Truncated Back-propagation for Bilevel Optimization AISTATS 2019
Learning to Find Common Objects Across Few Image Collections ICCV 2019
Learning Reactive Motion Policies in Multiple Task Spaces from Human Demonstrations CORL 2019
Trajectory-wise Control Variates for Variance Reduction in Policy Gradient Methods CORL 2019
Riemannian Motion Policy Fusion through Learnable Lyapunov Function Reshaping CORL 2019
Leveraging Experience in Lazy Search RSS 2019
Accelerating Imitation Learning with Predictive Models AISTATS 2019
Adversarial Imitation via Variational Inverse Reinforcement Learning ICLR 2019
Orthogonally Decoupled Variational Gaussian Processes NIPS 2018
Initialization matters: Orthogonal Predictive State Recurrent Neural Networks ICLR 2018
TRUNCATED HORIZON POLICY SEARCH: COMBINING REINFORCEMENT LEARNING & IMITATION LEARNING ICLR 2018
Learning and Inference in Hilbert Space with Quantum Graphical Models NIPS 2018
Differentiable MPC for End-to-end Planning and Control NIPS 2018
Dual Policy Iteration NIPS 2018
Agile Autonomous Driving using End-to-End Deep Imitation Learning RSS 2018
Convergence of Value Aggregation for Imitation Learning AISTATS 2018
Learning Hidden Quantum Markov Models AISTATS 2018
Learning from Conditional Distributions via Dual Embeddings AISTATS 2017
Variational Inference for Gaussian Process Models with Linear Complexity NIPS 2017
Exact Bounds on the Contact Driven Motion of a Sliding Object, With Applications to Robotic Pulling RSS 2017
Simultaneous Trajectory Estimation and Planning via Probabilistic Inference RSS 2017
Predictive-State Decoders: Encoding the Future into Recurrent Networks NIPS 2017
Predictive State Recurrent Neural Networks NIPS 2017
Prediction under Uncertainty in Sparse Spectrum Gaussian Processes with Applications to Filtering and Control ICML 2017
Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction ICML 2017
Towards Robust Skill Generalization: Unifying Learning from Demonstration and Motion Planning CORL 2017
Functional Gradient Motion Planning in Reproducing Kernel Hilbert Spaces RSS 2016
Learning to Filter with Predictive State Inference Machines ICML 2016
Inference Machines for Nonparametric Filter Learning IJCAI 2016
Incremental Variational Sparse Gaussian Process Regression NIPS 2016
Motion Planning as Probabilistic Inference using Gaussian Processes and Factor Graphs RSS 2016
The Nonparametric Kernel Bayes Smoother AISTATS 2016
Graph-Based Inverse Optimal Control for Robot Manipulation IJCAI 2015
A Spectral Learning Approach to Range-Only SLAM ICML 2013
Reduced-Rank Hidden Markov Models AISTATS 2010
Predictive State Temporal Difference Learning NIPS 2010
A Constraint Generation Approach to Learning Stable Linear Dynamical Systems NIPS 2007