La-MAML: Look-ahead Meta Learning for Continual Learning G Gupta, K Yadav, L Paull Accepted for Neurips 2020 (Oral), 2020 | 111* | 2020 |
Geometric consistency for self-supervised end-to-end visual odometry G Iyer, J Krishna Murthy, G Gupta, M Krishna, L Paull Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 58 | 2018 |
Towards view-invariant intersection recognition from videos using deep network ensembles A Kumar, G Gupta, A Sharma, KM Krishna 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2018 | 16 | 2018 |
Probabilistic object detection: Strengths, weaknesses, opportunities D Bhatt, D Bansal, G Gupta, H Lee, KM Jatavallabhula, L Paull Workshop on AI for Autonomous Driving at the International Conference on …, 2020 | 4 | 2020 |
Unifying variational inference and PAC-Bayes for supervised learning that scales S Thakur, H Van Hoof, G Gupta, D Meger arXiv preprint arXiv:1910.10367, 2019 | 4 | 2019 |
Can Active Sampling Reduce Causal Confusion in Offline Reinforcement Learning? G Gupta, TGJ Rudner, RT McAllister, A Gaidon, Y Gal NeurIPS ML Safety Workshop, CleaR conference 2023, 2023 | 1 | 2023 |
ReLU to the Rescue: Improve Your On-Policy Actor-Critic with Positive Advantages A Jesson, C Lu, G Gupta, A Filos, JN Foerster, Y Gal arXiv preprint arXiv:2306.01460, 2023 | | 2023 |
Can Active Sampling Reduce Causal Confusion in Offline Reinforcement Learning? G Gupta, TGJ Rudner, RT McAllister, A Gaidon, Y Gal 3rd Offline RL Workshop: Offline RL as a''Launchpad'', 2022 | | 2022 |