| Parameterizing neural power spectra into periodic and aperiodic components T Donoghue, M Haller, EJ Peterson, P Varma, P Sebastian, R Gao, T Noto, ... Nature neuroscience 23 (12), 1655-1665, 2020 | 1021 | 2020 |
| Snuba: Automating weak supervision to label training data P Varma, C Ré Proceedings of the VLDB Endowment. International Conference on Very Large …, 2018 | 173 | 2018 |
| Parameterizing neural power spectra. bioRxiv M Haller, T Donoghue, E Peterson, P Varma, P Sebastian, R Gao, T Noto, ... Epub ahead of print 11, 2018 | 166* | 2018 |
| Training Classifiers with Natural Language Explanations. P Liang, C Ré, B Hancock, P Varma, S Wang, M Bringmann ACL, 1884-1895, 2018 | 163* | 2018 |
| Weakly supervised classification of aortic valve malformations using unlabeled cardiac MRI sequences JA Fries, P Varma, VS Chen, K Xiao, H Tejeda, P Saha, J Dunnmon, ... Nature communications 10 (1), 1-10, 2019 | 130 | 2019 |
| Scene graph prediction with limited labels VS Chen, P Varma, R Krishna, M Bernstein, C Re, L Fei-Fei Proceedings of the IEEE International Conference on Computer Vision, 2580-2590, 2019 | 106 | 2019 |
| Learning dependency structures for weak supervision models P Varma, F Sala, A He, A Ratner, C Ré International Conference on Machine Learning, 6418-6427, 2019 | 73 | 2019 |
| Socratic Learning: Correcting Misspecified Generative Models using Discriminative Models P Varma, B He, D Iter, P Xu, R Yu, C De Sa, C Ré arXiv preprint arXiv:1610.08123, 2016 | 71* | 2016 |
| Weak Supervision: The New Programming Paradigm for Machine Learning A Ratner, S Bach, P Varma, C Ré Jul, 2017 | 67 | 2017 |
| Inferring Generative Model Structure with Static Analysis P Varma, BD He, P Bajaj, N Khandwala, I Banerjee, D Rubin, C Ré Advances in neural information processing systems, 240-250, 2017 | 61 | 2017 |
| Nonlinear Optimization Algorithm for Partially Coherent Phase Retrieval and Source Recovery J Zhong, L Tian, P Varma, L Waller IEEE Transactions on Computational Imaging 2 (3), 310-322, 2016 | 44 | 2016 |
| Parameterizing neural power spectra. biorxiv,(299859) M Haller, T Donoghue, E Peterson, P Varma, P Sebastian, R Gao, T Noto, ... | 39 | 2018 |
| Multi-resolution weak supervision for sequential data P Varma, F Sala, S Sagawa, J Fries, D Fu, S Khattar, A Ramamoorthy, ... Advances in Neural Information Processing Systems, 192-203, 2019 | 38 | 2019 |
| Flipper: A systematic approach to debugging training sets P Varma, D Iter, C De Sa, C Ré Proceedings of the 2nd Workshop on Human-in-the-Loop Data Analytics, 1-5, 2017 | 28 | 2017 |
| Cardiac Imaging of Aortic Valve Area from 34,287 UK Biobank Participants Reveal Novel Genetic Associations and Shared Genetic Comorbidity with Multiple Disease Phenotypes A Córdova-Palomera, C Tcheandjieu, J Fries, P Varma, VS Chen, ... Circulation: Genomic and Precision Medicine, 2020 | 22 | 2020 |
| Software 2.0 and Snorkel: Beyond Hand-Labeled Data C Ré Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018 | 14 | 2018 |
| Near-Eye Display Gaze Tracking via Convolutional Neural Networks R Konrad, S Shrestha, P Varma | 9* | |
| Multi-frame weak supervision to label wearable sensor data S Khattar, H O’Day, P Varma, J Fries, J Hicks, S Delp, H Bronte-Stewart, ... ICML Time Series Workshop, 2019 | 8 | 2019 |
| DEEM'22: Data Management for End-to-End Machine Learning M Boehm, P Varma, D Xin Proceedings of the 2022 International Conference on Management of Data, 2548 …, 2022 | 2 | 2022 |
| Cardiac imaging of aortic valve area from 26,142 UK Biobank participants reveal novel genetic associations and shared genetic comorbidity with multiple disease phenotypes A Córdova-Palomera, C Tcheandjieu, J Fries, P Varma, VS Chen, ... medRxiv, 2020 | 2 | 2020 |
Christopher RéComputer Science, Stanford University在 cs.stanford.edu 的电子邮件经过验证
