Divyansh Garg

According to our database, Divyansh Garg authored at least 12 papers between 2019 and 2024.

Collaborative distances:

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

2024

Agent Q: Advanced Reasoning and Learning for Autonomous AI Agents.

Pranav Putta, Edmund Mills, Naman Garg, Sumeet Motwani, Chelsea Finn, Divyansh Garg, Rafael Rafailov

CoRR, 2024

ROER: Regularized Optimal Experience Replay.

Changling Li, Zhang-Wei Hong, Pulkit Agrawal, Divyansh Garg, Joni Pajarinen

RLJ, 2024

2023

Learning to Detect Touches on Cluttered Tables.

Norberto Adrián Goussies, Kenji Hata, Shruthi Prabhakara, Abhishek Amit, Tony Aubé, Carl Cepress, Diana Chang, Li-Te Cheng, Horia Stefan Ciurdar, Mike Cleron, Chelsey Fleming, Ashwin Ganti, Divyansh Garg, Niloofar Gheissari, Petra Luna Grutzik, David Hendon, Daniel Iglesia, Jin Kim, Stuart Kyle, Chris LaRosa, Roman Lewkow, Peter F. McDermott, Chris Melancon, Paru Nackeeran, Neal Norwitz, Ali Rahimi, Brett Rampata, Carlos Sobrinho, George Sung, Natalie Zauhar, Palash Nandy

CoRR, 2023

Extreme Q-Learning: MaxEnt RL without Entropy.

Divyansh Garg, Joey Hejna, Matthieu Geist, Stefano Ermon

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Retrospective on the 2021 BASALT Competition on Learning from Human Feedback.

Rohin Shah, Steven H. Wang, Cody Wild, Stephanie Milani, Anssi Kanervisto, Vinicius G. Goecks, Nicholas R. Waytowich, David Watkins-Valls, Bharat Prakash, Edmund Mills, Divyansh Garg, Alexander Fries, Alexandra Souly, Jun Shern Chan, Daniel del Castillo, Tom Lieberum

CoRR, 2022

LISA: Learning Interpretable Skill Abstractions from Language.

Divyansh Garg, Skanda Vaidyanath, Kuno Kim, Jiaming Song, Stefano Ermon

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Retrospective on the 2021 MineRL BASALT Competition on Learning from Human Feedback.

Rohin Shah, Steven H. Wang, Cody Wild, Stephanie Milani, Anssi Kanervisto, Vinicius G. Goecks, Nicholas R. Waytowich, David Watkins-Valls, Bharat Prakash, Edmund Mills, Divyansh Garg, Alexander Fries, Alexandra Souly, Jun Shern Chan, Daniel del Castillo, Tom Lieberum

Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021

IQ-Learn: Inverse soft-Q Learning for Imitation.

Divyansh Garg, Shuvam Chakraborty, Chris Cundy, Jiaming Song, Stefano Ermon

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

2020

Wasserstein Distances for Stereo Disparity Estimation.

Divyansh Garg, Yan Wang, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger, Wei-Lun Chao

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving.

Yurong You, Yan Wang, Wei-Lun Chao, Divyansh Garg, Geoff Pleiss, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger

Proceedings of the 8th International Conference on Learning Representations, 2020

End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection.

Rui Qian, Divyansh Garg, Yan Wang, Yurong You, Serge J. Belongie, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger, Wei-Lun Chao

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Pseudo-LiDAR From Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving.

Yan Wang, Wei-Lun Chao, Divyansh Garg, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019