| 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 | 457 | 2023 |
| Machine translation: a literature review A Garg, M Agarwal arXiv preprint arXiv:1901.01122, 2018 | 47 | 2018 |
| Do current multi-task optimization methods in deep learning even help? D Xin, B Ghorbani, J Gilmer, A Garg, O Firat Advances in neural information processing systems 35, 13597-13609, 2022 | 39 | 2022 |
| Data scaling laws in NMT: The effect of noise and architecture Y Bansal, B Ghorbani, A Garg, B Zhang, C Cherry, B Neyshabur, O Firat International Conference on Machine Learning, 1466-1482, 2022 | 31 | 2022 |
| GROOV: A geographic routing over VANETs and its performance evaluation SK Dhurandher, MS Obaidat, D Bhardwaj, A Garg 2012 IEEE Global Communications Conference (GLOBECOM), 1670-1675, 2012 | 31 | 2012 |
| A loss curvature perspective on training instabilities of deep learning models J Gilmer, B Ghorbani, A Garg, S Kudugunta, B Neyshabur, D Cardoze, ... International Conference on Learning Representations, 2021 | 25 | 2021 |
| The devil is in the errors: Leveraging large language models for fine-grained machine translation evaluation P Fernandes, D Deutsch, M Finkelstein, P Riley, AFT Martins, G Neubig, ... arXiv preprint arXiv:2308.07286, 2023 | 23 | 2023 |
| Echo state speech recognition H Shrivastava, A Garg, Y Cao, Y Zhang, T Sainath ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 23 | 2021 |
| Hands-on one-shot learning with python: Learn to implement fast and accurate deep learning models with fewer training samples using pytorch S Jadon, A Garg Packt Publishing Ltd, 2020 | 11 | 2020 |
| The geometry of integration in text classification RNNs K Aitken, VV Ramasesh, A Garg, Y Cao, D Sussillo, N Maheswaranathan International Conference on Learning Representations, 2020 | 11 | 2020 |
| Efficient and Private Federated Learning with Partially Trainable Networks H Sidahmed, Z Xu, A Garg, Y Cao, M Chen New Frontiers in Federated Learning, NeurIPS, 2021 | 10 | 2021 |
| Wormhole attack prevention using clustering and digital signatures in reactive routing A Malhotra, D Bhardwaj, A Garg Proceedings of 2012 9th IEEE International Conference on Networking, Sensing …, 2012 | 9 | 2012 |
| Benchmarking neural network training algorithms GE Dahl, F Schneider, Z Nado, N Agarwal, CS Sastry, P Hennig, ... arXiv preprint arXiv:2306.07179, 2023 | 8 | 2023 |
| Binarized Neural Machine Translation Y Zhang, A Garg, Y Cao, L Lew, B Ghorbani, Z Zhang, O Firat Advances in Neural Information Processing Systems 36, 2024 | 4 | 2024 |
| Echo state neural machine translation A Garg, Y Cao, Q Ge arXiv preprint arXiv:2002.11847, 2020 | 4 | 2020 |
| A loss curvature perspective on training instability in deep learning J Gilmer, B Ghorbani, A Garg, SR Kudugunta, B Neyshabur, D Cardoze, ... | 1 | 2022 |
| Order Matters in the Presence of Dataset Imbalance for Multilingual Learning D Choi, D Xin, H Dadkhahi, J Gilmer, A Garg, O Firat, CK Yeh, AM Dai, ... Advances in Neural Information Processing Systems 36, 2024 | | 2024 |
| Federated Learning with Partially Trainable Networks H Sidahmed, Z Xu, M Chen, Y Cao, G Ankush US Patent App. 17/568,933, 2023 | | 2023 |
| Average sampling expansions from regular and irregular samples over shift-invariant subspaces on LCA groups P Devaraj, AK Garg Banach Journal of Mathematical Analysis 17 (1), 15, 2023 | | 2023 |
| Order Matters in the Presence of Dataset Imbalance for Multilingual Learning BG Dami Choi, Derrick Xin, Justin Gilmer, Hamid Dadkhahi, Ankush Garg, Orhan ... NeurIPS 2023, 2023 | | 2023 |
