Прати
Kyle Hsu
Kyle Hsu
Stanford University
Верификована је имејл адреса на cs.stanford.edu - Почетна страница
Наслов
Навело
Навело
Година
On the opportunities and risks of foundation models
R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ...
arXiv preprint arXiv:2108.07258, 2021
48122021
Open X-Embodiment: robotic learning datasets and RT-X models
OXE Collaboration
International Conference on Robotics and Automation (ICRA), 2024
475*2024
Unsupervised learning via meta-learning
K Hsu, S Levine, C Finn
International Conference on Learning Representations (ICLR), 2019
2982019
DROID: a large-scale in-the-wild robot manipulation dataset
A Khazatsky, K Pertsch, S Nair, A Balakrishna, S Dasari, S Karamcheti, ...
Robotics: Science and Systems (RSS), 2024
1212024
On the role of data in PAC-Bayes bounds
GK Dziugaite, K Hsu, W Gharbieh, G Arpino, DM Roy
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
1172021
Unsupervised curricula for visual meta-reinforcement learning
A Jabri, K Hsu, B Eysenbach, A Gupta, S Levine, C Finn
Neural Information Processing Systems (NeurIPS), 2019
792019
Multi-layered abstraction-based controller synthesis for continuous-time systems
K Hsu, R Majumdar, K Mallik, AK Schmuck
International Conference on Hybrid Systems: Computation and Control (HSCC), 2018
782018
Germanium wrap-around photodetectors on silicon photonics
R Going, TJ Seok, J Loo, K Hsu, MC Wu
Optics Express, 2015
522015
Evaluating real-world robot manipulation policies in simulation
X Li*, K Hsu*, J Gu*, K Pertsch, O Mees, HR Walke, C Fu, I Lunawat, ...
Conference on Robot Learning (CoRL), 2024
412024
Vision-based manipulators need to also see from their hands
K Hsu*, MJ Kim*, R Rafailov, J Wu, C Finn
International Conference on Learning Representations (ICLR), 2022
412022
Differentiable annealed importance sampling and the perils of gradient noise
G Zhang, K Hsu, J Li, C Finn, R Grosse
Neural Information Processing Systems (NeurIPS), 2021
382021
Lazy abstraction-based control for safety specifications
K Hsu, R Majumdar, K Mallik, AK Schmuck
Conference on Decision and Control (CDC), 2018
252018
Disentanglement via latent quantization
K Hsu, W Dorrell, JCR Whittington, J Wu, C Finn
Neural Information Processing Systems (NeurIPS), 2023
212023
Lazy abstraction-based controller synthesis
K Hsu, R Majumdar, K Mallik, AK Schmuck
International Symposium on Automated Technology for Verification and …, 2019
14*2019
Tripod: three complementary inductive biases for disentangled representation learning
K Hsu*, JI Hamid*, K Burns, C Finn, J Wu
International Conference on Machine Learning (ICML), 2024
52024
Range, not independence, drives modularity in biologically inspired representations
W Dorrell*, K Hsu*, L Hollingsworth, JH Lee, J Wu, C Finn, PE Latham, ...
arXiv preprint arXiv:2410.06232, 2024
2024
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