Ge Yang

According to our database, Ge Yang authored at least 14 papers between 2018 and 2024.

Collaborative distances:

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

2024

Rapid locomotion via reinforcement learning.

Gabriel B. Margolis, Ge Yang, Kartik Paigwar, Tao Chen, Pulkit Agrawal

Int. J. Robotics Res., 2024

2023

To the Noise and Back: Diffusion for Shared Autonomy.

Takuma Yoneda, Luzhe Sun, Ge Yang, Bradly C. Stadie, Matthew R. Walter

Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

Compositional Sculpting of Iterative Generative Processes.

Timur Garipov, Sebastiaan De Peuter, Ge Yang, Vikas Garg, Samuel Kaski, Tommi S. Jaakkola

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

2022

Bilinear value networks.

Zhang-Wei Hong, Ge Yang, Pulkit Agrawal

CoRR, 2022

Invariance Through Latent Alignment.

Takuma Yoneda, Ge Yang, Matthew R. Walter, Bradly C. Stadie

Proceedings of the Robotics: Science and Systems XVIII, New York City, NY, USA, June 27, 2022

Overcoming The Spectral Bias of Neural Value Approximation.

Ge Yang, Anurag Ajay, Pulkit Agrawal

Proceedings of the Tenth International Conference on Learning Representations, 2022

Bi-linear Value Networks for Multi-goal Reinforcement Learning.

Zhang-Wei Hong, Ge Yang, Pulkit Agrawal

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Invariance Through Inference.

Takuma Yoneda, Ge Yang, Matthew R. Walter, Bradly C. Stadie

CoRR, 2021

World Model as a Graph: Learning Latent Landmarks for Planning.

Lunjun Zhang, Ge Yang, Bradly C. Stadie

Proceedings of the 38th International Conference on Machine Learning, 2021

Learning Task Informed Abstractions.

Xiang Fu, Ge Yang, Pulkit Agrawal, Tommi S. Jaakkola

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Plan2Vec: Unsupervised Representation Learning by Latent Plans.

Ge Yang, Amy Zhang, Ari S. Morcos, Joelle Pineau, Pieter Abbeel, Roberto Calandra

Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

2018

Some Considerations on Learning to Explore via Meta-Reinforcement Learning.

Bradly C. Stadie, Ge Yang, Rein Houthooft, Xi Chen, Yan Duan, Yuhuai Wu, Pieter Abbeel, Ilya Sutskever

CoRR, 2018

The Importance of Sampling inMeta-Reinforcement Learning.

Bradly C. Stadie, Ge Yang, Rein Houthooft, Xi Chen, Yan Duan, Yuhuai Wu, Pieter Abbeel, Ilya Sutskever

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Learning Plannable Representations with Causal InfoGAN.

Thanard Kurutach, Aviv Tamar, Ge Yang, Stuart J. Russell, Pieter Abbeel

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018