| Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving Y Wang, WL Chao, D Garg, B Hariharan, M Campbell, K Weinberger IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 8445-8453, 2019 | 1277 | 2019 |
| Pseudo-lidar++: Accurate depth for 3d object detection in autonomous driving Y You, Y Wang, WL Chao, D Garg, G Pleiss, B Hariharan, M Campbell, ... International Conference on Learning Representations (ICLR) 2020, 2019 | 483 | 2019 |
| End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection R Qian, D Garg, Y Wang, Y You, S Belongie, B Hariharan, M Campbell, ... IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 5881-5890, 2020 | 246 | 2020 |
| IQ-Learn: Inverse soft-Q Learning for Imitation D Garg, S Chakraborty, C Cundy, J Song, S Ermon Advances In Neural Information Processing Systems (NeurIPS), 2021 | 184 | 2021 |
| Wasserstein Distances for Stereo Disparity Estimation D Garg, Y Wang, B Hariharan, M Campbell, KQ Weinberger, WL Chao Advances In Neural Information Processing Systems (NeurIPS), 2020 | 79 | 2020 |
| Extreme q-learning: Maxent rl without entropy D Garg, J Hejna, M Geist, S Ermon arXiv preprint arXiv:2301.02328, 2023 | 71 | 2023 |
| Agent q: Advanced reasoning and learning for autonomous ai agents P Putta, E Mills, N Garg, S Motwani, C Finn, D Garg, R Rafailov arXiv preprint arXiv:2408.07199, 2024 | 35 | 2024 |
| LISA: Learning interpretable skill abstractions from language D Garg, S Vaidyanath, K Kim, J Song, S Ermon Advances in Neural Information Processing Systems 35, 21711-21724, 2022 | 31 | 2022 |
| Retrospective on the 2021 minerl BASALT competition on learning from human feedback R Shah, SH Wang, C Wild, S Milani, A Kanervisto, VG Goecks, ... NeurIPS 2021 Competitions and Demonstrations Track, 259-272, 2022 | 9 | 2022 |
| Learning to detect touches on cluttered tables NA Goussies, K Hata, S Prabhakara, A Amit, T Aube, C Cepress, D Chang, ... arXiv preprint arXiv:2304.04687, 2023 | 3 | 2023 |
| Retrospective on the 2021 BASALT Competition on Learning from Human Feedback R Shah, SH Wang, C Wild, S Milani, A Kanervisto, VG Goecks, ... arXiv preprint arXiv:2204.07123, 2022 | 2 | 2022 |
| ROER: Regularized Optimal Experience Replay C Li, ZW Hong, P Agrawal, D Garg, J Pajarinen arXiv preprint arXiv:2407.03995, 2024 | 1 | 2024 |
| Systems and Methods for Imitation Learning D Garg US Patent App. 17/812,672, 2023 | 1 | 2023 |
| Comparative evaluation of one stage versus two stage surgical procedure for surgical extraction of bilaterally impacted mandibular third molars DS Garg, N Garg Scholars Journal of Applied Medical Sciences, 2527-2530, 2016 | 1 | 2016 |
| Systems and Methods for Automated Response to Natural Language Instructions D Garg, S Vaidyanath US Patent App. 18/172,969, 2023 | | 2023 |
| Agent Q: Combining Search, Self-Critique and Reinforcement Learning for Autonomous Web Agents P Putta, E Mills, N Garg, C Finn, D Garg, R Rafailov Workshop on Reinforcement Learning Beyond Rewards@ Reinforcement Learning …, 0 | | |
| Supplementary Material: Wasserstein Distances for Stereo Disparity Estimation D Garg, Y Wang, B Hariharan, M Campbell, KQ Weinberger, WL Chao | | |
| Supplementary Material: Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving Y Wang, WL Chao, D Garg, B Hariharan, M Campbell, KQ Weinberger | | |
Mark CampbellJohn A. Mellowes ‘60 Professor, Cornell UniversityBestätigte E-Mail-Adresse bei cornell.edu
