Using Neural Networks for Fast Reachable Set Computations. - Frank Jiang 003; Glen Chou; Mo Chen 001; Claire J. Tomlin (CoRR, 2016)

A hybrid framework for multi-vehicle collision avoidance. - Aparna Dhinakaran; Mo Chen 001; Glen Chou; Jennifer C. Shih; Claire J. Tomlin (CDC, 2017)

Learning Constraints from Demonstrations. - Glen Chou; Dmitry Berenson; Necmiye Ozay (WAFR, 2018)

Using Control Synthesis to Generate Corner Cases: A Case Study on Autonomous Driving. - Glen Chou; Yunus Emre Sahin; Liren Yang; Kwesi J. Rutledge; Petter Nilsson; Necmiye Ozay (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2018)

Learning Parametric Constraints in High Dimensions from Demonstrations. - Glen Chou; Necmiye Ozay; Dmitry Berenson (CoRL, 2019)

Uncertainty-Aware Constraint Learning for Adaptive Safe Motion Planning from Demonstrations. - Glen Chou; Dmitry Berenson; Necmiye Ozay (CoRL, 2020)

Explaining Multi-stage Tasks by Learning Temporal Logic Formulas from Suboptimal Demonstrations. - Glen Chou; Necmiye Ozay; Dmitry Berenson (Robotics: Science and Systems, 2020)

Planning with Learned Dynamics: Guaranteed Safety and Reachability via Lipschitz Constants. - Craig Knuth; Glen Chou; Necmiye Ozay; Dmitry Berenson (CoRR, 2020)

Learning Constraints From Locally-Optimal Demonstrations Under Cost Function Uncertainty. - Glen Chou; Necmiye Ozay; Dmitry Berenson (IEEE Robotics Autom. Lett., 2020)

Model Error Propagation via Learned Contraction Metrics for Safe Feedback Motion Planning of Unknown Systems. - Glen Chou; Necmiye Ozay; Dmitry Berenson (CDC, 2021)

Compositional safety rules for inter-triggering hybrid automata. - Kwesi J. Rutledge; Glen Chou; Necmiye Ozay (HSCC, 2021)

Inferring Obstacles and Path Validity from Visibility-Constrained Demonstrations. - Craig Knuth; Glen Chou; Necmiye Ozay; Dmitry Berenson (WAFR, 2021)

Learning constraints from demonstrations with grid and parametric representations. - Glen Chou; Dmitry Berenson; Necmiye Ozay (Int. J. Robotics Res., 2021)

Planning With Learned Dynamics: Probabilistic Guarantees on Safety and Reachability via Lipschitz Constants. - Craig Knuth; Glen Chou; Necmiye Ozay; Dmitry Berenson (IEEE Robotics Autom. Lett., 2021)

Safe Output Feedback Motion Planning from Images via Learned Perception Modules and Contraction Theory. - Glen Chou; Necmiye Ozay; Dmitry Berenson (WAFR, 2022)

Learning temporal logic formulas from suboptimal demonstrations: theory and experiments. - Glen Chou; Necmiye Ozay; Dmitry Berenson (Auton. Robots, 2022)

Gaussian Process Constraint Learning for Scalable Chance-Constrained Motion Planning From Demonstrations. - Glen Chou; Hao Wang 127; Dmitry Berenson (IEEE Robotics Autom. Lett., 2022)

Correction to "Planning With Learned Dynamics: Probabilistic Guarantees on Safety and Reachability Via Lipschitz Constants". - Craig Knuth; Glen Chou; Necmiye Ozay; Dmitry Berenson (IEEE Robotics Autom. Lett., 2022)

Synthesizing Stable Reduced-Order Visuomotor Policies for Nonlinear Systems via Sums-of-Squares Optimization. - Glen Chou; Russ Tedrake (CDC, 2023)

Fighting Uncertainty with Gradients: Offline Reinforcement Learning via Diffusion Score Matching. - H. J. Terry Suh; Glen Chou; Hongkai Dai; Lujie Yang; Abhishek Gupta; Russ Tedrake (CoRL, 2023)

Statistical Safety and Robustness Guarantees for Feedback Motion Planning of Unknown Underactuated Stochastic Systems. - Craig Knuth; Glen Chou; Jamie Reese; Joseph L. Moore (ICRA, 2023)

Data-Efficient Learning of Natural Language to Linear Temporal Logic Translators for Robot Task Specification. - Jiayi Pan 002; Glen Chou; Dmitry Berenson (ICRA, 2023)

Improving Out-of-Distribution Generalization of Learned Dynamics by Learning Pseudometrics and Constraint Manifolds. - Yating Lin; Glen Chou; Dmitry Berenson (ICRA, 2024)

Polar Hierarchical Mamba: Towards Streaming LiDAR Object Detection with Point Clouds as Egocentric Sequences. - Mellon M. Zhang; Glen Chou; Saibal Mukhopadhyay (CoRR, 2025)