Kyle Hsu

According to our database, Kyle Hsu authored at least 13 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Disentanglement via Latent Quantization.

Kyle Hsu, William Dorrell, James C. R. Whittington, Jiajun Wu, Chelsea Finn

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Extending Functionalities on a Web-based Portal for Research Computing.

Duy Pham, Kyle Hsu, Marinus Pennings, Tri Pham, Phi Au

Proceedings of the PEARC '22: Practice and Experience in Advanced Research Computing, Boston, MA, USA, July 10, 2022

Vision-Based Manipulators Need to Also See from Their Hands.

Kyle Hsu, Moo Jin Kim, Rafael Rafailov, Jiajun Wu, Chelsea Finn

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

On the Opportunities and Risks of Foundation Models.

Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ B. Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri S. Chatterji, Annie S. Chen, Kathleen Creel, Jared Quincy Davis, Dorottya Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren Gillespie, Karan Goel, Noah D. Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Koh, Mark S. Krass, Ranjay Krishna, Rohith Kuditipudi, et al.

CoRR, 2021

Differentiable Annealed Importance Sampling and the Perils of Gradient Noise.

Guodong Zhang, Kyle Hsu, Jianing Li, Chelsea Finn, Roger B. Grosse

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On the role of data in PAC-Bayes.

Gintare Karolina Dziugaite, Kyle Hsu, Waseem Gharbieh, Gabriel Arpino, Daniel M. Roy

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

On the role of data in PAC-Bayes bounds.

Gintare Karolina Dziugaite, Kyle Hsu, Waseem Gharbieh, Daniel M. Roy

CoRR, 2020

2019

Unsupervised Curricula for Visual Meta-Reinforcement Learning.

Allan Jabri, Kyle Hsu, Abhishek Gupta, Ben Eysenbach, Sergey Levine, Chelsea Finn

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Unsupervised Learning via Meta-Learning.

Kyle Hsu, Sergey Levine, Chelsea Finn

Proceedings of the 7th International Conference on Learning Representations, 2019

Lazy Abstraction-Based Controller Synthesis.

Kyle Hsu, Rupak Majumdar, Kaushik Mallik, Anne-Kathrin Schmuck

Proceedings of the Automated Technology for Verification and Analysis, 2019

2018

Lazy Abstraction-Based Control for Reachability.

Kyle Hsu, Rupak Majumdar, Kaushik Mallik, Anne-Kathrin Schmuck

CoRR, 2018

Multi-Layered Abstraction-Based Controller Synthesis for Continuous-Time Systems.

Kyle Hsu, Rupak Majumdar, Kaushik Mallik, Anne-Kathrin Schmuck

Proceedings of the 21st International Conference on Hybrid Systems: Computation and Control (part of CPS Week), 2018

Lazy Abstraction-Based Control for Safety Specifications.

Kyle Hsu, Rupak Majumdar, Kaushik Mallik, Anne-Kathrin Schmuck

Proceedings of the 57th IEEE Conference on Decision and Control, 2018