Divyansh Garg

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 18

Top Topics

Object Detection

Depth Estimation

Stereo Sequences

Autonomous Driving

Top Venues

Publications

Changling Li, Zhang-Wei Hong, Pulkit Agrawal, Divyansh Garg, Joni Pajarinen
ROER: Regularized Optimal Experience Replay. CoRR (2024)
Divyansh Garg, Joey Hejna, Matthieu Geist, Stefano Ermon
Extreme Q-Learning: MaxEnt RL without Entropy. ICLR (2023)
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
Learning to Detect Touches on Cluttered Tables. CoRR (2023)
Divyansh Garg, Joey Hejna, Matthieu Geist, Stefano Ermon
Extreme Q-Learning: MaxEnt RL without Entropy. CoRR (2023)
Divyansh Garg, Skanda Vaidyanath, Kuno Kim, Jiaming Song, Stefano Ermon
LISA: Learning Interpretable Skill Abstractions from Language. CoRR (2022)
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
Retrospective on the 2021 BASALT Competition on Learning from Human Feedback. CoRR (2022)
Divyansh Garg, Skanda Vaidyanath, Kuno Kim, Jiaming Song, Stefano Ermon
LISA: Learning Interpretable Skill Abstractions from Language. NeurIPS (2022)
Divyansh Garg, Shuvam Chakraborty, Chris Cundy, Jiaming Song, Stefano Ermon
IQ-Learn: Inverse soft-Q Learning for Imitation. NeurIPS (2021)
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
Retrospective on the 2021 MineRL BASALT Competition on Learning from Human Feedback. NeurIPS (Competition and Demos) (2021)
Divyansh Garg, Shuvam Chakraborty, Chris Cundy, Jiaming Song, Stefano Ermon
IQ-Learn: Inverse soft-Q Learning for Imitation. CoRR (2021)
Divyansh Garg, Yan Wang, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger, Wei-Lun Chao
Wasserstein Distances for Stereo Disparity Estimation. CoRR (2020)
Divyansh Garg, Yan Wang, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger, Wei-Lun Chao
Wasserstein Distances for Stereo Disparity Estimation. NeurIPS (2020)
Rui Qian, Divyansh Garg, Yan Wang, Yurong You, Serge J. Belongie, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger, Wei-Lun Chao
End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection. CVPR (2020)
Yurong You, Yan Wang, Wei-Lun Chao, Divyansh Garg, Geoff Pleiss, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger
Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving. ICLR (2020)
Rui Qian, Divyansh Garg, Yan Wang, Yurong You, Serge J. Belongie, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger, Wei-Lun Chao
End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection. CoRR (2020)
Yan Wang, Wei-Lun Chao, Divyansh Garg, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger
Pseudo-LiDAR From Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving. CVPR (2019)
Yurong You, Yan Wang, Wei-Lun Chao, Divyansh Garg, Geoff Pleiss, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger
Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving. CoRR (2019)
Yan Wang, Wei-Lun Chao, Divyansh Garg, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger
Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving. CoRR (2018)