| Gemini: A family of highly capable multimodal models G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ... arXiv preprint arXiv:2312.11805, 2023 | 1611 | 2023 |
| Actor-Attention-Critic for Multi-Agent Reinforcement Learning S Iqbal, F Sha Proceedings of the 36th International Conference on Machine Learning (ICML …, 2019 | 886 | 2019 |
| 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, 2024 | 412 | 2024 |
| Faster sorting algorithms discovered using deep reinforcement learning DJ Mankowitz, A Michi, A Zhernov, M Gelmi, M Selvi, C Paduraru, ... Nature 618 (7964), 257-263, 2023 | 142 | 2023 |
| Wearable Eye-tracking for Research: Automated dynamic gaze mapping and accuracy/precision comparisons across devices JJ MacInnes, S Iqbal, J Pearson, EN Johnson bioRxiv, 299925, 2018 | 96 | 2018 |
| Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning S Iqbal, CAS de Witt, B Peng, W Böhmer, S Whiteson, F Sha Proceedings of the 38th International Conference on Machine Learning (ICML), 2021 | 81* | 2021 |
| Coordinated Exploration via Intrinsic Rewards for Multi-Agent Reinforcement Learning S Iqbal, F Sha arXiv preprint arXiv:1905.12127, 2019 | 52 | 2019 |
| When MAML Can Adapt Fast and How to Assist When It Cannot S Arnold, S Iqbal, F Sha International Conference on Artificial Intelligence and Statistics (AISTATS …, 2021 | 31 | 2021 |
| Toward Sim-to-Real Directional Semantic Grasping S Iqbal, J Tremblay, T To, J Cheng, E Leitch, A Campbell, K Leung, ... International Conference on Robotics and Automation (ICRA), 7247-7253, 2020 | 28* | 2020 |
| A domain-agnostic approach for characterization of lifelong learning systems MM Baker, A New, M Aguilar-Simon, Z Al-Halah, SMR Arnold, ... Neural Networks 160, 274-296, 2023 | 22 | 2023 |
| ALMA: Hierarchical Learning for Composite Multi-Agent Tasks S Iqbal, R Costales, F Sha Advances in Neural Information Processing Systems 35, 7155-7166, 2022 | 10 | 2022 |
| Latent goal models for dynamic strategic interaction SN Iqbal, L Yin, CB Drucker, Q Kuang, JF Gariépy, ML Platt, JM Pearson PLOS Computational Biology 15 (3), e1006895, 2019 | 10 | 2019 |
| Training Language Models to Self-Correct via Reinforcement Learning A Kumar, V Zhuang, R Agarwal, Y Su, JD Co-Reyes, A Singh, K Baumli, ... arXiv preprint arXiv:2409.12917, 2024 | 9 | 2024 |
| Mobile Gaze Mapping: A Python package for mapping mobile gaze data to a fixed target stimulus J MacInnes, S Iqbal, J Pearson, E Johnson Journal of Open Source Software 3 (31), 984, 2018 | 8 | 2018 |
| Possibility Before Utility: Learning And Using Hierarchical Affordances R Costales, S Iqbal, F Sha International Conference on Learning Representations, 2021 | 4 | 2021 |
| A Goal-Based Movement Model for Continuous Multi-Agent Tasks S Iqbal, J Pearson NIPS BigNeuro Workshop, 2017 | 4 | 2017 |
| ROBOTIC CONTROL SYSTEM S Iqbal, J Tremblay, TH To, J Cheng, E Leitch, DJ Mckay, ST Birchfield US Patent App. 18/378,241, 2024 | | 2024 |
| Robotic control system S Iqbal, J Tremblay, TH To, J Cheng, E Leitch, DJ McKay, ST Birchfield US Patent 11,833,681, 2023 | | 2023 |
| Supplementary Material: Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning S Iqbal, CAS de Witt, B Peng, W Böhmer, S Whiteson, F Sha | | |
| Actor-Attention-Critic for Multi-Agent Reinforcement Learning Supplementary Material S Iqbal, F Sha | | |
Fei ShaGoogle ResearchVerified email at feisha.org
