Boots, Byron

82 publications

ICCV 2025 Details Matter for Indoor Open-Vocabulary 3D Instance Segmentation Sanghun Jung, Jingjing Zheng, Ke Zhang, Nan Qiao, Albert Y. C. Chen, Lu Xia, Chi Liu, Yuyin Sun, Xiao Zeng, Hsiang-Wei Huang, Byron Boots, Min Sun, Cheng-Hao Kuo

CoRL 2025 Long Range Navigator (LRN): Extending Robot Planning Horizons Beyond Metric Maps Matt Schmittle, Rohan Baijal, Nathan Hatch, Rosario Scalise, Mateo Guaman Castro, Sidharth Talia, Khimya Khetarpal, Byron Boots, Siddhartha Srinivasa

CoRL 2025 Self-Supervised Perception for Tactile Skin Covered Dexterous Hands Akash Sharma, Carolina Higuera, Chaithanya Krishna Bodduluri, Zixi Liu, Taosha Fan, Tess Hellebrekers, Mike Lambeta, Byron Boots, Michael Kaess, Tingfan Wu, Francois Robert Hogan, Mustafa Mukadam

CoRL 2025 Tactile Beyond Pixels: Multisensory Touch Representations for Robot Manipulation Carolina Higuera, Akash Sharma, Taosha Fan, Chaithanya Krishna Bodduluri, Byron Boots, Michael Kaess, Mike Lambeta, Tingfan Wu, Zixi Liu, Francois Robert Hogan, Mustafa Mukadam

CoRL 2025 Uncertainty-Aware Accurate Elevation Modeling for Off-Road Navigation via Neural Processes Sanghun Jung, Daehoon Gwak, Byron Boots, James Hays

CoRL 2025 Wheeled Lab: Modern Sim2Real for Low-Cost, Open-Source Wheeled Robotics Tyler Han, Preet Shah, Sidharth Rajagopal, Yanda Bao, Sanghun Jung, Sidharth Talia, Gabriel Guo, Bryan Xu, Bhaumik Mehta, Emma Romig, Rosario Scalise, Byron Boots

CoRL 2024 Avoid Everything: Model-Free Collision Avoidance with Expert-Guided Fine-Tuning Adam Fishman, Aaron Walsman, Mohak Bhardwaj, Wentao Yuan, Balakumar Sundaralingam, Byron Boots, Dieter Fox

ICML 2024 BeigeMaps: Behavioral Eigenmaps for Reinforcement Learning from Images Sandesh Adhikary, Anqi Li, Byron Boots

CoRL 2024 Sparsh: Self-Supervised Touch Representations for Vision-Based Tactile Sensing Carolina Higuera, Akash Sharma, Chaithanya Krishna Bodduluri, Taosha Fan, Patrick Lancaster, Mrinal Kalakrishnan, Michael Kaess, Byron Boots, Mike Lambeta, Tingfan Wu, Mustafa Mukadam

NeurIPS 2023 Adversarial Model for Offline Reinforcement Learning Mohak Bhardwaj, Tengyang Xie, Byron Boots, Nan Jiang, Ching-An Cheng

ICCV 2023 CAFA: Class-Aware Feature Alignment for Test-Time Adaptation Sanghun Jung, Jungsoo Lee, Nanhee Kim, Amirreza Shaban, Byron Boots, Jaegul Choo

CoRL 2023 CAJun: Continuous Adaptive Jumping Using a Learned Centroidal Controller Yuxiang Yang, Guanya Shi, Xiangyun Meng, Wenhao Yu, Tingnan Zhang, Jie Tan, Byron Boots

L4DC 2023 Continuous Versatile Jumping Using Learned Action Residuals Yuxiang Yang, Xiangyun Meng, Wenhao Yu, Tingnan Zhang, Jie Tan, Byron Boots

CoRL 2023 DATT: Deep Adaptive Trajectory Tracking for Quadrotor Control Kevin Huang, Rwik Rana, Alexander Spitzer, Guanya Shi, Byron Boots

CoRL 2023 DYNAMO-GRASP: DYNAMics-Aware Optimization for GRASP Point Detection in Suction Grippers Boling Yang, Soofiyan Atar, Markus Grotz, Byron Boots, Joshua Smith

ICCV 2023 LiDAR-UDA: Self-Ensembling Through Time for Unsupervised LiDAR Domain Adaptation Amirreza Shaban, JoonHo Lee, Sanghun Jung, Xiangyun Meng, Byron Boots

ICML 2023 MAHALO: Unifying Offline Reinforcement Learning and Imitation Learning from Observations Anqi Li, Byron Boots, Ching-An Cheng

WACV 2022 Few-Shot Weakly-Supervised Object Detection via Directional Statistics Amirreza Shaban, Amir Rahimi, Thalaiyasingam Ajanthan, Byron Boots, Richard Hartley

CoRL 2022 Learning Sampling Distributions for Model Predictive Control Jacob Sacks, Byron Boots

CoRL 2022 Learning Semantics-Aware Locomotion Skills from Human Demonstration Yuxiang Yang, Xiangyun Meng, Wenhao Yu, Tingnan Zhang, Jie Tan, Byron Boots

NeurIPSW 2022 Learning Semantics-Aware Locomotion Skills from Human Demonstrations Yuxiang Yang, Xiangyun Meng, Wenhao Yu, Tingnan Zhang, Jie Tan, Byron Boots

CoRL 2022 Motion Policy Networks Adam Fishman, Adithyavairavan Murali, Clemens Eppner, Bryan Peele, Byron Boots, Dieter Fox

AISTATS 2021 Quantum Tensor Networks, Stochastic Processes, and Weighted Automata Sandesh Adhikary, Siddarth Srinivasan, Jacob Miller, Guillaume Rabusseau, Byron Boots

ICLR 2021 Blending MPC & Value Function Approximation for Efficient Reinforcement Learning Mohak Bhardwaj, Sanjiban Choudhury, Byron Boots

UAI 2021 Explaining Fast Improvement in Online Imitation Learning Xinyan Yan, Byron Boots, Ching-An Cheng

CoRL 2021 Fast and Efficient Locomotion via Learned Gait Transitions Yuxiang Yang, Tingnan Zhang, Erwin Coumans, Jie Tan, Byron Boots

CoRL 2021 Motivating Physical Activity via Competitive Human-Robot Interaction Boling Yang, Golnaz Habibi, Patrick Lancaster, Byron Boots, Joshua Smith

CoRL 2021 STORM: An Integrated Framework for Fast Joint-Space Model-Predictive Control for Reactive Manipulation Mohak Bhardwaj, Balakumar Sundaralingam, Arsalan Mousavian, Nathan D. Ratliff, Dieter Fox, Fabio Ramos, Byron Boots

ICML 2021 Safe Reinforcement Learning Using Advantage-Based Intervention Nolan C Wagener, Byron Boots, Ching-An Cheng

CoRL 2021 Semantic Terrain Classification for Off-Road Autonomous Driving Amirreza Shaban, Xiangyun Meng, JoonHo Lee, Byron Boots, Dieter Fox

AISTATS 2020 A Reduction from Reinforcement Learning to No-Regret Online Learning Ching-An Cheng, Remi Tachet Combes, Byron Boots, Geoff Gordon

ICLR 2020 Composing Task-Agnostic Policies with Deep Reinforcement Learning Ahmed H. Qureshi, Jacob J. Johnson, Yuzhe Qin, Taylor Henderson, Byron Boots, Michael C. Yip

L4DC 2020 Euclideanizing Flows: Diffeomorphic Reduction for Learning Stable Dynamical Systems Muhammad Asif Rana, Anqi Li, Dieter Fox, Byron Boots, Fabio Ramos, Nathan Ratliff

AISTATS 2020 Expressiveness and Learning of Hidden Quantum Markov Models Sandesh Adhikary, Siddarth Srinivasan, Geoff Gordon, Byron Boots

L4DC 2020 Information Theoretic Model Predictive Q-Learning Mohak Bhardwaj, Ankur Handa, Dieter Fox, Byron Boots

NeurIPS 2020 Intra Order-Preserving Functions for Calibration of Multi-Class Neural Networks Amir Rahimi, Amirreza Shaban, Ching-An Cheng, Richard Hartley, Byron Boots

CoRL 2020 Learning a Contact-Adaptive Controller for Robust, Efficient Legged Locomotion Xingye Da, Zhaoming Xie, David Hoeller, Byron Boots, Anima Anandkumar, Yuke Zhu, Buck Babich, Animesh Garg

AISTATS 2020 Online Learning with Continuous Variations: Dynamic Regret and Reductions Ching-An Cheng, Jonathan Lee, Ken Goldberg, Byron Boots

ECCV 2020 Pairwise Similarity Knowledge Transfer for Weakly Supervised Object Localization Amir Rahimi, Amirreza Shaban, Thalaiyasingam Ajanthan, Richard Hartley, Byron Boots

CoRL 2020 Stein Variational Model Predictive Control Alexander Lambert, Fabio Ramos, Byron Boots, Dieter Fox, Adam Fishman

AISTATS 2019 Accelerating Imitation Learning with Predictive Models Ching-An Cheng, Xinyan Yan, Evangelos Theodorou, Byron Boots

ICLR 2019 Adversarial Imitation via Variational Inverse Reinforcement Learning Ahmed H. Qureshi, Byron Boots, Michael C. Yip

CoRL 2019 Learning Reactive Motion Policies in Multiple Task Spaces from Human Demonstrations M. Asif Rana, Anqi Li, Harish Ravichandar, Mustafa Mukadam, Sonia Chernova, Dieter Fox, Byron Boots, Nathan Ratliff

ICML 2019 Predictor-Corrector Policy Optimization Ching-An Cheng, Xinyan Yan, Nathan Ratliff, Byron Boots

ICML 2019 Provably Efficient Imitation Learning from Observation Alone Wen Sun, Anirudh Vemula, Byron Boots, Drew Bagnell

CoRL 2019 Riemannian Motion Policy Fusion Through Learnable Lyapunov Function Reshaping Mustafa Mukadam, Ching-An Cheng, Dieter Fox, Byron Boots, Nathan Ratliff

CoRL 2019 Trajectory-Wise Control Variates for Variance Reduction in Policy Gradient Methods Ching-An Cheng, Xinyan Yan, Byron Boots

AISTATS 2019 Truncated Back-Propagation for Bilevel Optimization Amirreza Shaban, Ching-An Cheng, Nathan Hatch, Byron Boots

AISTATS 2018 Convergence of Value Aggregation for Imitation Learning Ching-An Cheng, Byron Boots

NeurIPS 2018 Differentiable MPC for End-to-End Planning and Control Brandon Amos, Ivan Jimenez, Jacob Sacks, Byron Boots, J. Zico Kolter

NeurIPS 2018 Dual Policy Iteration Wen Sun, Geoffrey J. Gordon, Byron Boots, J. Bagnell

UAI 2018 Fast Policy Learning Through Imitation and Reinforcement Ching-An Cheng, Xinyan Yan, Nolan Wagener, Byron Boots

ICLR 2018 Initialization Matters: Orthogonal Predictive State Recurrent Neural Networks Krzysztof Choromanski, Carlton Downey, Byron Boots

AISTATS 2018 Learning Hidden Quantum Markov Models Siddarth Srinivasan, Geoffrey J. Gordon, Byron Boots

NeurIPS 2018 Learning and Inference in Hilbert Space with Quantum Graphical Models Siddarth Srinivasan, Carlton Downey, Byron Boots

NeurIPS 2018 Orthogonally Decoupled Variational Gaussian Processes Hugh Salimbeni, Ching-An Cheng, Byron Boots, Marc Deisenroth

ICLR 2018 Truncated Horizon Policy Search: Combining Reinforcement Learning & Imitation Learning Wen Sun, J. Andrew Bagnell, Byron Boots

ICML 2017 Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction Wen Sun, Arun Venkatraman, Geoffrey J. Gordon, Byron Boots, J. Andrew Bagnell

AISTATS 2017 Learning from Conditional Distributions via Dual Embeddings Bo Dai, Niao He, Yunpeng Pan, Byron Boots, Le Song

ICML 2017 Prediction Under Uncertainty in Sparse Spectrum Gaussian Processes with Applications to Filtering and Control Yunpeng Pan, Xinyan Yan, Evangelos A. Theodorou, Byron Boots

NeurIPS 2017 Predictive State Recurrent Neural Networks Carlton Downey, Ahmed Hefny, Byron Boots, Geoffrey J. Gordon, Boyue Li

NeurIPS 2017 Predictive-State Decoders: Encoding the Future into Recurrent Networks Arun Venkatraman, Nicholas Rhinehart, Wen Sun, Lerrel Pinto, Martial Hebert, Byron Boots, Kris Kitani, J. Bagnell

AAAI 2017 Sampling Beats Fixed Estimate Predictors for Cloning Stochastic Behavior in Multiagent Systems Brian Hrolenok, Byron Boots, Tucker Hybinette Balch

CoRL 2017 Towards Robust Skill Generalization: Unifying Learning from Demonstration and Motion Planning Muhammad Asif Rana, Mustafa Mukadam, Seyed Reza Ahmadzadeh, Sonia Chernova, Byron Boots

NeurIPS 2017 Variational Inference for Gaussian Process Models with Linear Complexity Ching-An Cheng, Byron Boots

NeurIPS 2016 Incremental Variational Sparse Gaussian Process Regression Ching-An Cheng, Byron Boots

IJCAI 2016 Inference Machines for Nonparametric Filter Learning Arun Venkatraman, Wen Sun, Martial Hebert, Byron Boots, J. Andrew Bagnell

ICML 2016 Learning to Filter with Predictive State Inference Machines Wen Sun, Arun Venkatraman, Byron Boots, J.Andrew Bagnell

UAI 2016 Learning to Smooth with Bidirectional Predictive State Inference Machines Wen Sun, Roberto Capobianco, Geoffrey J. Gordon, J. Andrew Bagnell, Byron Boots

AAAI 2016 Online Instrumental Variable Regression with Applications to Online Linear System Identification Arun Venkatraman, Wen Sun, Martial Hebert, J. Andrew Bagnell, Byron Boots

AISTATS 2016 The Nonparametric Kernel Bayes Smoother Yu Nishiyama, Amir Afsharinejad, Shunsuke Naruse, Byron Boots, Le Song

IJCAI 2015 Graph-Based Inverse Optimal Control for Robot Manipulation Arunkumar Byravan, Mathew Monfort, Brian D. Ziebart, Byron Boots, Dieter Fox

UAI 2015 Learning Latent Variable Models by Improving Spectral Solutions with Exterior Point Method Amirreza Shaban, Mehrdad Farajtabar, Bo Xie, Le Song, Byron Boots

ICML 2013 A Spectral Learning Approach to Range-Only SLAM Byron Boots, Geoff Gordon

UAI 2013 Hilbert Space Embeddings of Predictive State Representations Byron Boots, Geoffrey J. Gordon, Arthur Gretton

ICML 2012 Two Manifold Problems with Applications to Nonlinear System Identification Byron Boots, Geoffrey J. Gordon

AAAI 2011 An Online Spectral Learning Algorithm for Partially Observable Nonlinear Dynamical Systems Byron Boots, Geoffrey J. Gordon

ICML 2010 Hilbert Space Embeddings of Hidden Markov Models Le Song, Byron Boots, Sajid M. Siddiqi, Geoffrey J. Gordon, Alexander J. Smola

NeurIPS 2010 Predictive State Temporal Difference Learning Byron Boots, Geoffrey J. Gordon

AISTATS 2010 Reduced-Rank Hidden Markov Models Sajid Siddiqi, Byron Boots, Geoffrey Gordon

NeurIPS 2007 A Constraint Generation Approach to Learning Stable Linear Dynamical Systems Byron Boots, Geoffrey J. Gordon, Sajid M. Siddiqi

AAAI 2005 DC-SSAT: A Divide-and-Conquer Approach to Solving Stochastic Satisfiability Problems Efficiently Stephen M. Majercik, Byron Boots