Yue, Yisong

Monograph from CaltechAUTHORS

• Israel, Uriah and Marks, Markus, et el. (2024) A Foundation Model for Cell Segmentation; bioRvix; 2023.11.17.567630; PMCID PMC10690226; 10.1101/2023.11.17.567630
• Talukder, Sabera and Yue, Yisong, et el. (2024) TOTEM: TOkenized Time Series EMbeddings for General Time Series Analysis; 10.48550/arxiv.2402.16412
• Voloshin, Cameron and Verma, Abhinav, et el. (2023) Eventual Discounting Temporal Logic Counterfactual Experience Replay
• Huang, Yujia and Jimenez Rodriguez, Ivan Dario, et el. (2022) FI-ODE: Certified and Robust Forward Invariance in Neural ODEs; 10.48550/arXiv.2210.16940
• Sun, Jennifer J. and Tjandrasuwita, Megan, et el. (2022) Neurosymbolic Programming for Science; 10.48550/arXiv.2210.05050
• Sun, Jennifer J. and Ulmer, Andrew, et el. (2022) The MABe22 Benchmarks for Representation Learning of Multi-Agent Behavior; 10.48550/arXiv.2207.10553
• Tucker, Maegan and Li, Kejun, et el. (2022) POLAR: Preference Optimization and Learning Algorithms for Robotics; 10.48550/arXiv.2208.04404
• Sun, Jennifer J. and Karashchuk, Pierre, et el. (2022) BKinD-3D: Self-Supervised 3D Keypoint Discovery from Multi-View Videos; 10.48550/arXiv.2212.07401
• Dorobantu, Victor D. and Azizzadenesheli, Kamyar, et el. (2022) Compactly Restrictable Metric Policy Optimization Problems; 10.48550/arXiv.arXiv.2207.05850
• Voloshin, Cameron and Le, Hoang M., et el. (2022) Policy Optimization with Linear Temporal Logic Constraints; 10.48550/arXiv.arXiv.2206.09546
• Talukder, Sabera and Sun, Jennifer J., et el. (2022) Deep Neural Imputation: A Framework for Recovering Incomplete Brain Recordings; 10.48550/arXiv.arXiv.2206.08094
• Taylor, Andrew J. and Dorobantu, Victor D., et el. (2022) Safety of Sampled-Data Systems with Control Barrier Functions via Approximate Discrete Time Models; 10.48550/arXiv.2203.11470
• Cosner, Ryan K. and Jimenez Rodriguez, Ivan D., et el. (2022) Self-Supervised Online Learning for Safety-Critical Control using Stereo Vision; 10.48550/arXiv.2203.01404
• Zhan, Eric and Sun, Jennifer J., et el. (2022) Unsupervised Learning of Neurosymbolic Encoders; 10.48550/arXiv.2107.13132
• Sun, Jennifer J. and Ryou, Serim, et el. (2022) Self-Supervised Keypoint Discovery in Behavioral Videos; 10.48550/arXiv.2112.05121
• Cosner, Ryan K. and Tucker, Maegan, et el. (2022) Safety-Aware Preference-Based Learning for Safety-Critical Control; 10.48550/arXiv.2112.08516
• Bernstein, Jeremy and Farhang, Alex, et el. (2022) Kernel Interpolation as a Bayes Point Machine; 10.48550/arXiv.2110.04274
• Tseng, Albert and Sun, Jennifer J., et el. (2022) Automatic Synthesis of Diverse Weak Supervision Sources for Behavior Analysis; 10.48550/arXiv.2111.15186
• Tjandrasuwita, Megan and Sun, Jennifer J., et el. (2022) Interpreting Expert Annotation Differences in Animal Behavior; 10.48550/arXiv.2106.06114
• Jimenez Rodriguez, Ivan Dario and Ames, Aaron D., et el. (2022) LyaNet: A Lyapunov Framework for Training Neural ODEs; 10.48550/arXiv.2202.02526
• Ferber, Aaron and Song, Jialin, et el. (2021) Learning Pseudo-Backdoors for Mixed Integer Programs; 10.48550/arXiv.2106.05080
• Yin, Tianwei and Wu, Zihui, et el. (2021) End-to-End Sequential Sampling and Reconstruction for MR Imaging; 10.48550/arXiv.2105.06460
• Sun, Jennifer J. and Karigo, Tomomi, et el. (2021) The Multi-Agent Behavior Dataset: Mouse Dyadic Social Interactions; 10.48550/arXiv.2104.02710
• Bernstein, Jeremy and Yue, Yisong (2021) Computing the Information Content of Trained Neural Networks; 10.48550/arXiv.2103.01045
• Liu, Anqi and Liu, Hao, et el. (2021) Disentangling Observed Causal Effects from Latent Confounders using Method of Moments; 10.48550/arXiv.2101.06614
• Talukder, Sabera and Raghavan, Guruprasad, et el. (2021) Architecture Agnostic Neural Networks; 10.48550/arXiv.2011.02712
• Barnum, George and Talukder, Sabera, et el. (2021) On the Benefits of Early Fusion in Multimodal Representation Learning; 10.48550/arXiv.2011.07191
• Kumar, Akash and Singla, Adish, et el. (2020) Average-case Complexity of Teaching Convex Polytopes via Halfspace Queries; 10.48550/arXiv.2006.14677
• Ryou, Serim and Maser, Michael R., et el. (2020) Graph Neural Networks for the Prediction of Substrate-Specific Organic Reaction Conditions; 10.48550/arXiv.2007.04275
• Yu, Chenkai and Shi, Guanya, et el. (2020) Competitive Control with Delayed Imperfect Information; 10.48550/arXiv.2010.11637
• Shah, Ameesh and Zhan, Eric, et el. (2020) Learning Differentiable Programs with Admissible Neural Heuristics; 10.48550/arXiv.2007.12101
• Marino, Joseph and Piché, Alexandre, et el. (2020) Iterative Amortized Policy Optimization; 10.48550/arXiv.2010.10670
• Wang, Haoxuan and Liu, Anqi, et el. (2020) Distributionally Robust Learning for Unsupervised Domain Adaptation; 10.48550/arXiv.2010.05784
• Prajapat, Manish and Azizzadenesheli, Kamyar, et el. (2020) Competitive Policy Optimization; 10.48550/arXiv.2006.10611
• Yu, Chenkai and Shi, Guanya, et el. (2020) The Power of Predictions in Online Control; 10.48550/arXiv.2006.07569
• Song, Jialin and Lanka, Ravi, et el. (2020) A General Large Neighborhood Search Framework for Solving Integer Programs; 10.48550/arXiv.2004.00422
• Bernstein, Jeremy and Vahdat, Arash, et el. (2020) On the distance between two neural networks and the stability of learning; 10.48550/arXiv.2002.03432
• Shi, Guanya and Lin, Yiheng, et el. (2020) Online Optimization with Memory and Competitive Control; 10.48550/arXiv.2002.05318
• Park, Jung Yeon and Carr, Kenneth Theo, et el. (2020) Multiresolution Tensor Learning for Efficient and Interpretable Spatial Analysis; 10.48550/arXiv.2002.05578
• Voloshin, Cameron and Le, Hoang M., et el. (2020) Empirical Study of Off-Policy Policy Evaluation for Reinforcement Learning; 10.48550/arXiv.1911.06854
• Liu, Anqi and Liu, Hao, et el. (2020) Triply Robust Off-Policy Evaluation; 10.48550/arXiv.1911.05811
• Zhan, Eric and Tseng, Albert, et el. (2020) Learning Calibratable Policies using Programmatic Style-Consistency; 10.48550/arXiv.1910.01179
• Liu, Anqi and Shi, Guanya, et el. (2019) Robust Regression for Safe Exploration in Control; 10.48550/arXiv.1906.05819
• Song, Jialin and Lanka, Ravi, et el. (2019) Co-training for Policy Learning; 10.48550/arXiv.1907.04484
• Sui, Yanan and Zhuang, Vincent, et el. (2019) Multi-dueling Bandits with Dependent Arms; 10.48550/arXiv.1705.00253
• Dathathri, Sumanth and Zheng, Stephan, et el. (2019) Detecting Adversarial Examples via Neural Fingerprinting; 10.48550/arXiv.1803.03870
• Yu, Rose and Zheng, Stephan, et el. (2019) Long-term Forecasting using Tensor-Train RNNs; 10.48550/arXiv.1711.00073
• Song, Jialin and Lanka, Ravi, et el. (2019) Learning to Search via Retrospective Imitation; 10.48550/arXiv.1804.00846
• Sui, Yanan and Yue, Yisong, et el. (2019) Correlational Dueling Bandits with Application to Clinical Treatment in Large Decision Spaces; 10.48550/arXiv.1707.02375
• Song, Jialin and Tokpanov, Yury S., et el. (2019) Optimizing Photonic Nanostructures via Multi-fidelity Gaussian Processes; 10.48550/arXiv.1811.07707
• Sha, Long and Lucey, Patrick, et el. (2019) Fine-Grained Retrieval of Sports Plays using Tree-Based Alignment of Trajectories; 10.48550/arXiv.1710.02255
• Zhan, Eric and Zheng, Stephan, et el. (2019) Generative Multi-Agent Behavioral Cloning; 10.48550/arXiv.1803.07612
• Zheng, Stephan and Yu, Rose, et el. (2018) Multi-resolution Tensor Learning for Large-Scale Spatial Data; 10.48550/arXiv.1802.06825