Voloshin, Cameron; Verma, Abhinav et al. (2023) Eventual Discounting Temporal Logic Counterfactual Experience Replay arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20230316-204049328
Sun, Jennifer J.; Karashchuk, Pierre et al. (2022) BKinD-3D: Self-Supervised 3D Keypoint Discovery from Multi-View Videos arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20221219-204745839
Huang, Yujia; Jimenez Rodriguez, Ivan Dario et al. (2022) FI-ODE: Certified and Robust Forward Invariance in Neural ODEs arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20221219-234122405
Sun, Jennifer J.; Tjandrasuwita, Megan et al. (2022) Neurosymbolic Programming for Science arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20221219-234119032
Tucker, Maegan; Li, Kejun et al. (2022) POLAR: Preference Optimization and Learning Algorithms for Robotics arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20221219-234115665
Sun, Jennifer J.; Ulmer, Andrew et al. (2022) The MABe22 Benchmarks for Representation Learning of Multi-Agent Behavior arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20221219-234042044
Dorobantu, Victor D.; Azizzadenesheli, Kamyar et al. (2022) Compactly Restrictable Metric Policy Optimization Problems arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20220714-212414777
Voloshin, Cameron; Le, Hoang M. et al. (2022) Policy Optimization with Linear Temporal Logic Constraints arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20220714-212419626
Talukder, Sabera; Sun, Jennifer J. et al. (2022) Deep Neural Imputation: A Framework for Recovering Incomplete Brain Recordings arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20220714-212423144
Taylor, Andrew J.; Dorobantu, Victor D. et al. (2022) Safety of Sampled-Data Systems with Control Barrier Functions via Approximate Discrete Time Models arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20220325-224027516
Cosner, Ryan K.; Jimenez Rodriguez, Ivan D. et al. (2022) Self-Supervised Online Learning for Safety-Critical Control using Stereo Vision arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20220325-220806703
Jimenez Rodriguez, Ivan Dario; Ames, Aaron D. et al. (2022) LyaNet: A Lyapunov Framework for Training Neural ODEs arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20220224-200943137
Cosner, Ryan K.; Tucker, Maegan et al. (2021) Safety-Aware Preference-Based Learning for Safety-Critical Control arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20220224-200843937
Sun, Jennifer J.; Ryou, Serim et al. (2021) Self-Supervised Keypoint Discovery in Behavioral Videos arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20220224-200833645
Tseng, Albert; Sun, Jennifer J. et al. (2021) Automatic Synthesis of Diverse Weak Supervision Sources for Behavior Analysis arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20220224-200830238
Bernstein, Jeremy; Farhang, Alex et al. (2021) Kernel Interpolation as a Bayes Point Machine arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20220224-200822492
Zhan, Eric; Sun, Jennifer J. et al. (2021) Unsupervised Learning of Neurosymbolic Encoders arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20220224-200805115
Tjandrasuwita, Megan; Sun, Jennifer J. et al. (2021) Interpreting Expert Annotation Differences in Animal Behavior arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20220224-200758198
Ferber, Aaron; Song, Jialin et al. (2021) Learning Pseudo-Backdoors for Mixed Integer Programs arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20210719-210128990
Yin, Tianwei; Wu, Zihui et al. (2021) End-to-End Sequential Sampling and Reconstruction for MR Imaging arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20210604-142545306
Sun, Jennifer J.; Karigo, Tomomi et al. (2021) The Multi-Agent Behavior Dataset: Mouse Dyadic Social Interactions arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20210510-093610124
Bernstein, Jeremy; Yue, Yisong (2021) Computing the Information Content of Trained Neural Networks arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20210304-095340677
Liu, Anqi; Liu, Hao et al. (2021) Disentangling Observed Causal Effects from Latent Confounders using Method of Moments arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20210225-132714927
Barnum, George; Talukder, Sabera et al. (2020) On the Benefits of Early Fusion in Multimodal Representation Learning arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20210119-161629149
Talukder, Sabera; Raghavan, Guruprasad et al. (2020) Architecture Agnostic Neural Networks arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20210119-161636048
Yu, Chenkai; Shi, Guanya et al. (2020) Competitive Control with Delayed Imperfect Information arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20201110-082106076
Marino, Joseph; Piché, Alexandre et al. (2020) Iterative Amortized Policy Optimization arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20201110-082336091
Wang, Haoxuan; Liu, Anqi et al. (2020) Distributionally Robust Learning for Unsupervised Domain Adaptation arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20201106-120148344
Shah, Ameesh; Zhan, Eric et al. (2020) Learning Differentiable Programs with Admissible Neural Heuristics arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20201110-085241409
Ryou, Serim; Maser, Michael R. et al. (2020) Graph Neural Networks for the Prediction of Substrate-Specific Organic Reaction Conditions arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20201110-154207213
Kumar, Akash; Singla, Adish et al. (2020) Average-case Complexity of Teaching Convex Polytopes via Halfspace Queries arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20201111-071759033
Prajapat, Manish; Azizzadenesheli, Kamyar et al. (2020) Competitive Policy Optimization arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20201106-120215567
Yu, Chenkai; Shi, Guanya et al. (2020) The Power of Predictions in Online Control arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20200707-094715120
Song, Jialin; Lanka, Ravi et al. (2020) A General Large Neighborhood Search Framework for Solving Integer Programs arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20200526-151215262
Park, Jung Yeon; Carr, Kenneth Theo et al. (2020) Multiresolution Tensor Learning for Efficient and Interpretable Spatial Analysis arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20200214-105610460
Shi, Guanya; Lin, Yiheng et al. (2020) Online Optimization with Memory and Competitive Control arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20200214-105606928
Bernstein, Jeremy; Vahdat, Arash et al. (2020) On the distance between two neural networks and the stability of learning arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20200214-105602886
Voloshin, Cameron; Le, Hoang M. et al. (2019) Empirical Study of Off-Policy Policy Evaluation for Reinforcement Learning arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20200109-100747650
Liu, Anqi; Liu, Hao et al. (2019) Triply Robust Off-Policy Evaluation arXiv; https://resolver.caltech.edu/CaltechAUTHORS:20200109-085907638
Zhan, Eric; Tseng, Albert et al. (2019) Learning Calibratable Policies using Programmatic Style-Consistency arXiv; https://doi.org/10.48550/arXiv.1910.01179
Song, Jialin; Lanka, Ravi et al. (2019) Co-training for Policy Learning arXiv; https://doi.org/10.48550/arXiv.1907.04484
Liu, Anqi; Shi, Guanya et al. (2019) Robust Regression for Safe Exploration in Control arXiv; https://doi.org/10.48550/arXiv.1906.05819
Song, Jialin; Tokpanov, Yury S. et al. (2018) Optimizing Photonic Nanostructures via Multi-fidelity Gaussian Processes arXiv; In: 32nd Conference on Neural Information Processing Systems Workshop on Machine Learning for Molecules (NIPS 2018), 2-8 December 2018, Montréal, Canada https://doi.org/10.48550/arXiv.1811.07707 (Submitted)
Song, Jialin; Lanka, Ravi et al. (2018) Learning to Search via Retrospective Imitation arXiv; https://doi.org/10.48550/arXiv.1804.00846 (Submitted)
Zhan, Eric; Zheng, Stephan et al. (2018) Generative Multi-Agent Behavioral Cloning arXiv; https://doi.org/10.48550/arXiv.1803.07612 (Submitted)
Dathathri, Sumanth; Zheng, Stephan et al. (2018) Detecting Adversarial Examples via Neural Fingerprinting arXiv; https://doi.org/10.48550/arXiv.1803.03870 (Submitted)
Zheng, Stephan; Yu, Rose et al. (2018) Multi-resolution Tensor Learning for Large-Scale Spatial Data https://doi.org/10.48550/arXiv.1802.06825 (Submitted)
Yu, Rose; Zheng, Stephan et al. (2017) Long-term Forecasting using Tensor-Train RNNs arXiv; https://doi.org/10.48550/arXiv.1711.00073 (Submitted)
Sha, Long; Lucey, Patrick et al. (2017) Fine-Grained Retrieval of Sports Plays using Tree-Based Alignment of Trajectories arXiv; In: 11th ACM International Conference on Web Search and Data Mining (WSDM’18), 5-9 February 2018, Los Angeles, CA https://doi.org/10.48550/arXiv.1710.02255 (Submitted)
Sui, Yanan; Yue, Yisong et al. (2017) Correlational Dueling Bandits with Application to Clinical Treatment in Large Decision Spaces arXiv; https://doi.org/10.48550/arXiv.1707.02375 (Submitted)
Sui, Yanan; Zhuang, Vincent et al. (2017) Multi-dueling Bandits with Dependent Arms arXiv; https://doi.org/10.48550/arXiv.1705.00253