| An Optimistic Perspective on Offline Reinforcement Learning R Agarwal, D Schuurmans, M Norouzi International Conference on Machine Learning (ICML), 2020 | 667* | 2020 |
| Deep Reinforcement Learning at the Edge of the Statistical Precipice R Agarwal, M Schwarzer, PS Castro, A Courville, MG Bellemare Neural Information Processing Systems (NeurIPS), 𝗢𝘂𝘁𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 𝗣𝗮𝗽𝗲𝗿 𝗔𝘄𝗮𝗿𝗱, 2021 | 625 | 2021 |
| Neural additive models: Interpretable machine learning with neural nets R Agarwal, L Melnick, Frosst, Zhang, Lengerich, R Caruana, GE Hinton Neural Information Processing Systems (NeurIPS), 𝗦𝗽𝗼𝘁𝗹𝗶𝗴𝗵𝘁, 2021 | 471 | 2021 |
| Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context M Reid, N Savinov, D Teplyashin, D Lepikhin, T Lillicrap, J Alayrac, ... arXiv preprint arXiv:2403.05530, *Core Contributor, 2024 | 377 | 2024 |
| Revisiting Fundamentals of Experience Replay W Fedus*, P Ramachandran*, R Agarwal, Y Bengio, H Larochelle, ... International Conference on Machine Learning (ICML), 2020 | 299 | 2020 |
| Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning R Agarwal, MC Machado, PS Castro, MG Bellemare International Conference on Learning Representations (ICLR), 𝗦𝗽𝗼𝘁𝗹𝗶𝗴𝗵𝘁, 2021 | 199 | 2021 |
| RL Unplugged: A Collection of Benchmarks for Offline Reinforcement Learning C Gulcehre, Z Wang, A Novikov, T Paine, S Gómez, K Zolna, R Agarwal, ... Advances in Neural Information Processing Systems (NeurIPS), 2020 | 196* | 2020 |
| Learning to Generalize from Sparse and Underspecified Rewards R Agarwal, C Liang, D Schuurmans, M Norouzi International Conference on Machine Learning (ICML), 2019 | 108 | 2019 |
| Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning A Kumar*, R Agarwal*, D Ghosh, S Levine International Conference on Learning Representations (ICLR), *equal contribution, 2021 | 97 | 2021 |
| On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes R Agarwal*, N Vieillard*, Y Zhou, P Stanczyk, S Ramos, M Geist, ... International Conference on Learning Representations (ICLR), 2024 | 77* | 2024 |
| Reincarnating Reinforcement Learning: Reusing Prior Computation to Accelerate Progress R Agarwal, M Schwarzer, PS Castro, A Courville, MG Bellemare Neural Information Processing Systems (NeurIPS), 2022 | 68* | 2022 |
| Bigger, Better, Faster: Human-level Atari with human-level efficiency M Schwarzer, JO Ceron, Courville, Bellemare, PS Castro*, R Agarwal* International Conference on Machine Learning (ICML), 2023 | 56 | 2023 |
| DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization A Kumar, R Agarwal, T Ma, A Courville, G Tucker, S Levine International Conference on Learning Representations (ICLR), 𝗦𝗽𝗼𝘁𝗹𝗶𝗴𝗵𝘁, 2022 | 56 | 2022 |
| Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research C Gulino, J Fu, W Luo, G Tucker, E Bronstein, Y Lu, J Harb, X Pan, ... Neural Information Processing Systems, NeurIPS, 2023 | 55 | 2023 |
| Gemma 2: Improving open language models at a practical size G Team, M Riviere, S Pathak, PG Sessa, C Hardin, S Bhupatiraju, ... arXiv preprint arXiv:2408.00118, 2024 | 51 | 2024 |
| The Dormant Neuron Phenomenon in Deep Reinforcement Learning G Sokar, R Agarwal, PS Castro, U Evci International Conference on Machine Learning (ICML), 𝐎𝐫𝐚𝐥, 2023 | 51 | 2023 |
| Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models A Singh*, JD Co-Reyes*, R Agarwal*, A Anand, P Patil, PJ Liu, J Harrison, ... Transactions on Machine Learning Research (TMLR), 2024 | 46 | 2024 |
| Offline Q-Learning on Diverse Multi-Task Data Both Scales And Generalizes A Kumar, R Agarwal, X Geng, G Tucker, S Levine International Conference on Learning Representations (ICLR), 𝐍𝐨𝐭𝐚𝐛𝐥𝐞-𝐭𝐨𝐩-𝟓%, 2023 | 43 | 2023 |
| Distillspec: Improving speculative decoding via knowledge distillation Y Zhou, K Lyu, AS Rawat, AK Menon, ..., S Kumar, JF Kagy, R Agarwal International Conference on Learning Representations (ICLR), 2024 | 37 | 2024 |
| On the Generalization of Representations in Reinforcement Learning CL Lan, S Tu, A Oberman, R Agarwal, MG Bellemare International Conference on Artificial Intelligence and Statistics (AISTATS), 2022 | 35 | 2022 |
Marc G. BellemareReliant AIZweryfikowany adres z reliant.ai
