| Meta-learning requires meta-augmentation J Rajendran, A Irpan, E Jang Neural Information Processing Systems (NeurIPS), 2020 | 103 | 2020 |
| Discovery of useful questions as auxiliary tasks V Veeriah, M Hessel, Z Xu, R Lewis, J Rajendran, J Oh, H van Hasselt, ... Neural Information Processing Systems (NeurIPS), 2019 | 95 | 2019 |
| Attend, adapt and transfer: Attentive deep architecture for adaptive transfer from multiple sources in the same domain J Rajendran, A Srinivas, MM Khapra, P Prasanna, B Ravindran International Conference on Learning Representations (ICLR), 2017 | 82* | 2017 |
| Bridge correlational neural networks for multilingual multimodal representation learning J Rajendran, MM Khapra, S Chandar, B Ravindran North American Chapter of the Association of Computational Linguistics (NAACL), 2016 | 72 | 2016 |
| Learning end-to-end goal-oriented dialog with multiple answers J Rajendran, J Ganhotra, S Singh, L Polymenakos Empirical Methods in Natural Language Processing (EMNLP), 2018 | 34 | 2018 |
| Understanding the impact of COVID-19 on online mental health forums L Biester, K Matton, J Rajendran, EM Provost, R Mihalcea ACM Transactions on Management Information Systems (TMIS) 12 (4), 1-28, 2021 | 32 | 2021 |
| Quantifying the effects of COVID-19 on mental health support forums L Biester, K Matton, J Rajendran, EM Provost, R Mihalcea Workshop on NLP for COVID-19 at EMNLP, 2020 | 28 | 2020 |
| Learning end-to-end goal-oriented dialog with maximal user task success and minimal human agent use J Rajendran, J Ganhotra, LC Polymenakos Transactions of the Association for Computational Linguistics (TACL) 7, 375-386, 2019 | 17 | 2019 |
| A correlational encoder decoder architecture for pivot based sequence generation A Saha, MM Khapra, S Chandar, J Rajendran, K Cho International Conference on Computational Linguistics (COLING), 2016 | 17 | 2016 |
| Reinforcement Learning of Implicit and Explicit Control Flow in Instructions EA Brooks, J Rajendran, RL Lewis, S Singh International Conference on Machine Learning (ICML), 2021 | 16 | 2021 |
| An introduction to lifelong supervised learning S Sodhani, M Faramarzi, SV Mehta, P Malviya, M Abdelsalam, ... arXiv preprint arXiv:2207.04354, 2022 | 15 | 2022 |
| Towards Evaluating Adaptivity of Model-Based Reinforcement Learning Methods Y Wan, A Rahimi-Kalahroudi, J Rajendran, I Momennejad, S Chandar, ... International Conference on Machine Learning (ICML), 22536-22561, 2022 | 14 | 2022 |
| How Should an Agent Practice? J Rajendran, R Lewis, V Veeriah, H Lee, S Singh AAAI Conference on Artificial Intelligence (AAAI) 34 (04), 5454-5461, 2020 | 11 | 2020 |
| Dealing With Non-stationarity in Decentralized Cooperative Multi-Agent Deep Reinforcement Learning via Multi-Timescale Learning H Nekoei, A Badrinaaraayanan, A Sinha, M Amini, J Rajendran, ... Conference on Lifelong Learning Agents (CoLLAs), 2023 | 10 | 2023 |
| Mastering memory tasks with world models MR Samsami, A Zholus, J Rajendran, S Chandar International Conference on Learning Representations (ICLR), 2024 | 8 | 2024 |
| Learning conditional policies for crystal design using offline reinforcement learning P Govindarajan, S Miret, J Rector-Brooks, M Phielipp, J Rajendran, ... Digital Discovery 3 (4), 769-785, 2024 | 2 | 2024 |
| Replay Buffer with Local Forgetting for Adapting to Local Environment Changes in Deep Model-Based Reinforcement Learning A Rahimi-Kalahroudi, J Rajendran, I Momennejad, H van Seijen, ... Conference on Lifelong Learning Agents, 21-42, 2023 | 2* | 2023 |
| Conditionally Optimistic Exploration for Cooperative Deep Multi-Agent Reinforcement Learning X Zhao, Y Pan, C Xiao, S Chandar, J Rajendran Conference on Uncertainty in Artificial Intelligence (UAI), 2023 | 2 | 2023 |
| Behavioral Cloning for Crystal Design P Govindarajan, S Miret, J Rector-Brooks, M Phielipp, J Rajendran, ... Workshop on Machine Learning for Materials at ICLR, 2023 | 2 | 2023 |
| NE-Table: A Neural key-value table for Named Entities J Rajendran, J Ganhotra, X Guo, M Yu, S Singh, L Polymenakos Recent Advances in Natural Language Processing (RANLP), 2019 | 2* | 2019 |
Sarath ChandarAssociate Professor @ Polytechnique Montreal. Mila. Canada CIFAR AI Chair. Canada Research Chair.Verified email at polymtl.ca
