| Deep speech 2: End-to-end speech recognition in english and mandarin D Amodei, S Ananthanarayanan, R Anubhai, J Bai, E Battenberg, C Case, ... International conference on machine learning, 173-182, 2016 | 3915 | 2016 |
| fastMRI: An open dataset and benchmarks for accelerated MRI J Zbontar, F Knoll, A Sriram, T Murrell, Z Huang, MJ Muckley, A Defazio, ... arXiv preprint arXiv:1811.08839, 2018 | 969 | 2018 |
| Open catalyst 2020 (OC20) dataset and community challenges L Chanussot, A Das, S Goyal, T Lavril, M Shuaibi, M Riviere, K Tran, ... Acs Catalysis 11 (10), 6059-6072, 2021 | 578 | 2021 |
| Mls: A large-scale multilingual dataset for speech research V Pratap, Q Xu, A Sriram, G Synnaeve, R Collobert arXiv preprint arXiv:2012.03411, 2020 | 533 | 2020 |
| fastMRI: A publicly available raw k-space and DICOM dataset of knee images for accelerated MR image reconstruction using machine learning F Knoll, J Zbontar, A Sriram, MJ Muckley, M Bruno, A Defazio, M Parente, ... Radiology. Artificial intelligence 2 (1), 2020 | 423 | 2020 |
| End-to-end variational networks for accelerated MRI reconstruction A Sriram, J Zbontar, T Murrell, A Defazio, CL Zitnick, N Yakubova, F Knoll, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 357 | 2020 |
| Cold fusion: Training seq2seq models together with language models A Sriram, H Jun, S Satheesh, A Coates arXiv preprint arXiv:1708.06426, 2017 | 352 | 2017 |
| Results of the 2020 fastMRI challenge for machine learning MR image reconstruction MJ Muckley, B Riemenschneider, A Radmanesh, S Kim, G Jeong, J Ko, ... IEEE transactions on medical imaging 40 (9), 2306-2317, 2021 | 286 | 2021 |
| End-to-end asr: from supervised to semi-supervised learning with modern architectures G Synnaeve, Q Xu, J Kahn, T Likhomanenko, E Grave, V Pratap, A Sriram, ... arXiv preprint arXiv:1911.08460, 2019 | 285 | 2019 |
| Exploring neural transducers for end-to-end speech recognition E Battenberg, J Chen, R Child, A Coates, YGY Li, H Liu, S Satheesh, ... 2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU …, 2017 | 263 | 2017 |
| Robust wav2vec 2.0: Analyzing domain shift in self-supervised pre-training WN Hsu, A Sriram, A Baevski, T Likhomanenko, Q Xu, V Pratap, J Kahn, ... arXiv preprint arXiv:2104.01027, 2021 | 259 | 2021 |
| FRED (A Framework for Reconstructing Epidemic Dynamics): an open-source software system for modeling infectious diseases and control strategies using census-based populations JJ Grefenstette, ST Brown, R Rosenfeld, J DePasse, NTB Stone, ... BMC public health 13, 1-14, 2013 | 243 | 2013 |
| Advancing machine learning for MR image reconstruction with an open competition: Overview of the 2019 fastMRI challenge F Knoll, T Murrell, A Sriram, N Yakubova, J Zbontar, M Rabbat, A Defazio, ... Magnetic resonance in medicine 84 (6), 3054-3070, 2020 | 240 | 2020 |
| Medical Image Computing and Computer-Assisted Intervention–MICCAI 2011 Y Wang, J Nie, PT Yap, F Shi, L Guo, D Shen Proceedings of the 24th International Conference, Strasbourg, France 27, 2011 | 187 | 2011 |
| Massively multilingual ASR: 50 languages, 1 model, 1 billion parameters V Pratap, A Sriram, P Tomasello, A Hannun, V Liptchinsky, G Synnaeve, ... arXiv preprint arXiv:2007.03001, 2020 | 161 | 2020 |
| Using deep learning to accelerate knee MRI at 3 T: results of an interchangeability study MP Recht, J Zbontar, DK Sodickson, F Knoll, N Yakubova, A Sriram, ... American Journal of Roentgenology 215 (6), 1421-1429, 2020 | 154 | 2020 |
| The Open Catalyst 2022 (OC22) dataset and challenges for oxide electrocatalysts R Tran, J Lan, M Shuaibi, BM Wood, S Goyal, A Das, J Heras-Domingo, ... ACS Catalysis 13 (5), 3066-3084, 2023 | 150 | 2023 |
| GrappaNet: Combining parallel imaging with deep learning for multi-coil MRI reconstruction A Sriram, J Zbontar, T Murrell, CL Zitnick, A Defazio, DK Sodickson Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 127 | 2020 |
| An introduction to electrocatalyst design using machine learning for renewable energy storage CL Zitnick, L Chanussot, A Das, S Goyal, J Heras-Domingo, C Ho, W Hu, ... arXiv preprint arXiv:2010.09435, 2020 | 94 | 2020 |
| Rotation invariant graph neural networks using spin convolutions M Shuaibi, A Kolluru, A Das, A Grover, A Sriram, Z Ulissi, CL Zitnick arXiv preprint arXiv:2106.09575, 2021 | 85 | 2021 |
C. Lawrence ZitnickFAIR (Meta)Verifierad e-postadress på fb.com
