| 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 | 1490 | 2023 |
| Experience replay for continual learning D Rolnick, A Ahuja, J Schwarz, T Lillicrap, G Wayne Advances in neural information processing systems 32, 2019 | 1053 | 2019 |
| Genomic features of response to combination immunotherapy in patients with advanced non-small-cell lung cancer MD Hellmann, T Nathanson, H Rizvi, BC Creelan, F Sanchez-Vega, ... Cancer cell 33 (5), 843-852. e4, 2018 | 965 | 2018 |
| 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 | 358 | 2024 |
| Contribution of systemic and somatic factors to clinical response and resistance to PD-L1 blockade in urothelial cancer: an exploratory multi-omic analysis A Snyder, T Nathanson, SA Funt, A Ahuja, J Buros Novik, MD Hellmann, ... PLoS medicine 14 (5), e1002309, 2017 | 300 | 2017 |
| Unsupervised predictive memory in a goal-directed agent G Wayne, CC Hung, D Amos, M Mirza, A Ahuja, A Grabska-Barwinska, ... arXiv preprint arXiv:1803.10760, 2018 | 199 | 2018 |
| Neural probabilistic motor primitives for humanoid control J Merel, L Hasenclever, A Galashov, A Ahuja, V Pham, G Wayne, YW Teh, ... arXiv preprint arXiv:1811.11711, 2018 | 157 | 2018 |
| Somatic mutations and neoepitope homology in melanomas treated with CTLA-4 blockade T Nathanson, A Ahuja, A Rubinsteyn, BA Aksoy, MD Hellmann, D Miao, ... Cancer immunology research 5 (1), 84-91, 2017 | 147 | 2017 |
| Optimizing agent behavior over long time scales by transporting value CC Hung, T Lillicrap, J Abramson, Y Wu, M Mirza, F Carnevale, A Ahuja, ... Nature communications 10 (1), 5223, 2019 | 136 | 2019 |
| Experimental observation of plasma wakefield growth driven by the seeded self-modulation of a proton bunch M Turner, E Adli, A Ahuja, O Apsimon, R Apsimon, AM Bachmann, ... Physical review letters 122 (5), 054801, 2019 | 135 | 2019 |
| Rethinking data-intensive science using scalable analytics systems FA Nothaft, M Massie, T Danford, Z Zhang, U Laserson, C Yeksigian, ... Proceedings of the 2015 ACM SIGMOD International Conference on Management of …, 2015 | 126 | 2015 |
| Catch & carry: reusable neural controllers for vision-guided whole-body tasks J Merel, S Tunyasuvunakool, A Ahuja, Y Tassa, L Hasenclever, V Pham, ... ACM Transactions on Graphics (TOG) 39 (4), 39: 1-39: 12, 2020 | 122 | 2020 |
| V-mpo: On-policy maximum a posteriori policy optimization for discrete and continuous control HF Song, A Abdolmaleki, JT Springenberg, A Clark, H Soyer, JW Rae, ... arXiv preprint arXiv:1909.12238, 2019 | 116 | 2019 |
| Hierarchical visuomotor control of humanoids J Merel, A Ahuja, V Pham, S Tunyasuvunakool, S Liu, D Tirumala, ... arXiv preprint arXiv:1811.09656, 2018 | 114 | 2018 |
| Imitating interactive intelligence J Abramson, A Ahuja, I Barr, A Brussee, F Carnevale, M Cassin, ... arXiv preprint arXiv:2012.05672, 2020 | 70 | 2020 |
| Learning Representations for Weakly Supervised Natural Language Processing Tasks F Huang, A Ahuja, D Downey, Y Yang, Y Guo, A Yates | 66 | 2013 |
| Collaborating with language models for embodied reasoning I Dasgupta, C Kaeser-Chen, K Marino, A Ahuja, S Babayan, F Hill, ... arXiv preprint arXiv:2302.00763, 2023 | 53 | 2023 |
| Exploiting hierarchy for learning and transfer in kl-regularized rl D Tirumala, H Noh, A Galashov, L Hasenclever, A Ahuja, G Wayne, ... arXiv preprint arXiv:1903.07438, 2019 | 44 | 2019 |
| Creating multimodal interactive agents with imitation and self-supervised learning DMIA Team, J Abramson, A Ahuja, A Brussee, F Carnevale, M Cassin, ... arXiv preprint arXiv:2112.03763, 2021 | 43 | 2021 |
| Chemotherapy weakly contributes to predicted neoantigen expression in ovarian cancer T O’Donnell, EL Christie, A Ahuja, J Buros, BA Aksoy, DDL Bowtell, ... BMC cancer 18, 1-11, 2018 | 42 | 2018 |
