Byron Boots

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