| 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 | 2795 | 2016 |
| 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), e190007, 2020 | 450* | 2020 |
| Cold fusion: Training seq2seq models together with language models A Sriram, H Jun, S Satheesh, A Coates arXiv preprint arXiv:1708.06426, 2017 | 218 | 2017 |
| Exploring neural transducers for end-to-end speech recognition E Battenberg, J Chen, R Child, A Coates, YGY Li, H Liu, S Satheesh, ... Automatic Speech Recognition and Understanding Workshop (ASRU), 206-213, 2017 | 205* | 2017 |
| 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), 1-14, 2013 | 185 | 2013 |
| 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 | 158 | 2019 |
| 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 | 105 | 2020 |
| 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 | 90 | 2020 |
| 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 | 84 | 2021 |
| End-to-end variational networks for accelerated MRI reconstruction A Sriram, J Zbontar, T Murrell, A Defazio, CL Zitnick, N Yakubova, F Knoll, ... International Conference on Medical Image Computing and Computer-Assisted …, 2020 | 76 | 2020 |
| 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 | 61 | 2020 |
| 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 | 57 | 2021 |
| 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 | 57 | 2021 |
| Robust speech recognition using generative adversarial networks A Sriram, H Jun, Y Gaur, S Satheesh 2018 IEEE international conference on acoustics, speech and signal …, 2018 | 54 | 2018 |
| 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 | 53 | 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, ... AJR. American journal of roentgenology 215 (6), 1421, 2020 | 52 | 2020 |
| Covid-19 prognosis via self-supervised representation learning and multi-image prediction A Sriram, M Muckley, K Sinha, F Shamout, J Pineau, KJ Geras, L Azour, ... arXiv preprint arXiv:2101.04909, 2021 | 31 | 2021 |
| State-of-the-art machine learning MRI reconstruction in 2020: Results of the second fastMRI challenge M Muckley, B Riemenschneider, A Radmanesh, S Kim, G Jeong, J Ko, ... | 28 | 2020 |
| RNN-T for latency controlled ASR with improved beam search M Jain, K Schubert, J Mahadeokar, CF Yeh, K Kalgaonkar, A Sriram, ... arXiv preprint arXiv:1911.01629, 2019 | 26 | 2019 |
| 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 | 22 | 2020 |
Sanjeev SatheeshStanford UniversityZweryfikowany adres z stanford.edu
