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Tianhe Yu
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Cited by
Year
Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning
T Yu, D Quillen, Z He, R Julian, K Hausman, C Finn, S Levine
Conference on Robot Learning (CoRL), 2019
8782019
Gradient Surgery for Multi-Task Learning
T Yu, S Kumar, A Gupta, S Levine, K Hausman, C Finn
Neural Information Processing Systems (NeurIPS), 2020
7802020
PaLM-E: An Embodied Multimodal Language Model
D Driess, F Xia, MSM Sajjadi, C Lynch, A Chowdhery, B Ichter, A Wahid, ...
International Conference on Machine Learning (ICML), 2023
7342023
Real-time user-guided image colorization with learned deep priors
R Zhang, JY Zhu, P Isola, X Geng, AS Lin, T Yu, AA Efros
ACM Transactions on Graphics (TOG) 36 (4), 119:1--119:11, 2017
6992017
MOPO: Model-based Offline Policy Optimization
T Yu, G Thomas, L Yu, S Ermon, J Zou, S Levine, C Finn, T Ma
Neural Information Processing Systems (NeurIPS), 2020
6742020
One-shot visual imitation learning via meta-learning
C Finn*, T Yu*, T Zhang, P Abbeel, S Levine
Conference on Robot Learning (CoRL), 2017
5882017
One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning
T Yu, C Finn, A Xie, S Dasari, T Zhang, P Abbeel, S Levine
Robotics: Science and Systems (RSS), 2018
3922018
RT-1: Robotics Transformer for Real-World Control at Scale
A Brohan, N Brown, J Carbajal, Y Chebotar, J Dabis, C Finn, ...
Robotics: Science and Systems (RSS), 2023
3862023
Gemini: a family of highly capable multimodal models
G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ...
arXiv preprint arXiv:2312.11805, 2023
3482023
COMBO: Conservative Offline Model-Based Policy Optimization
T Yu, A Kumar, R Rafailov, A Rajeswaran, S Levine, C Finn
Neural Information Processing Systems (NeurIPS), 2021
3122021
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
A Brohan, N Brown, J Carbajal, Y Chebotar, X Chen, K Choromanski, ...
arXiv preprint arXiv:2307.15818, 2023
2462023
Efficiently Identifying Task Groupings for Multi-Task Learning
C Fifty, E Amid, Z Zhao, T Yu, R Anil, C Finn
Neural Information Processing Systems (NeurIPS), 2021
1902021
Offline Reinforcement Learning from Images with Latent Space Models
R Rafailov*, T Yu*, A Rajeswaran, C Finn
Learning for Dynamics and Control (L4DC), 1154-1168, 2021
1102021
Generalizing Skills with Semi-Supervised Reinforcement Learning
C Finn, T Yu, J Fu, P Abbeel, S Levine
International Conference on Learning Representations (ICLR), 2016
802016
Meta-Inverse Reinforcement Learning with Probabilistic Context Variables
L Yu*, T Yu*, C Finn, S Ermon
Neural Information Processing Systems (NeurIPS), 2019
742019
Open X-Embodiment: Robotic learning datasets and RT-X models
A Padalkar, A Pooley, A Jain, A Bewley, A Herzog, A Irpan, A Khazatsky, ...
arXiv preprint arXiv:2310.08864, 2023
662023
Conservative Data Sharing for Multi-Task Offline Reinforcement Learning
T Yu, A Kumar, Y Chebotar, K Hausman, S Levine, C Finn
Neural Information Processing Systems (NeurIPS), 2021
662021
One-Shot Hierarchical Imitation Learning of Compound Visuomotor Tasks
T Yu, P Abbeel, S Levine, C Finn
International Conference on Intelligent Robots and Systems (IROS), 2018
642018
How to Leverage Unlabeled Data in Offline Reinforcement Learning
T Yu, A Kumar, Y Chebotar, K Hausman, C Finn, S Levine
International Conference on Machine Learning (ICML), 2022
482022
Scaling Robot Learning with Semantically Imagined Experience
T Yu, T Xiao, A Stone, J Tompson, A Brohan, S Wang, J Singh, C Tan, ...
arXiv preprint arXiv:2302.11550, 2023
472023
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Articles 1–20