| On the opportunities and risks of foundation models R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... arXiv preprint arXiv:2108.07258, 2021 | 4802 | 2021 |
| Hogwild: A lock-free approach to parallelizing stochastic gradient descent F Niu, B Recht, C Ré, S Wright Advances in Neural Information Processing Systems, 693-701, 2011 | 2830* | 2011 |
| Flashattention: Fast and memory-efficient exact attention with io-awareness T Dao, D Fu, S Ermon, A Rudra, C Ré Advances in Neural Information Processing Systems 35, 16344-16359, 2022 | 1731 | 2022 |
| Efficiently modeling long sequences with structured state spaces A Gu, K Goel, C Ré arXiv preprint arXiv:2111.00396, 2021 | 1646 | 2021 |
| Snorkel: Rapid training data creation with weak supervision A Ratner, SH Bach, H Ehrenberg, J Fries, S Wu, C Ré Proceedings of the VLDB endowment. International conference on very large …, 2017 | 1454 | 2017 |
| Holistic evaluation of language models P Liang, R Bommasani, T Lee, D Tsipras, D Soylu, M Yasunaga, Y Zhang, ... arXiv preprint arXiv:2211.09110, 2022 | 1191 | 2022 |
| Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features KH Yu, C Zhang, GJ Berry, RB Altman, C Ré, DL Rubin, M Snyder Nature communications 7 (1), 12474, 2016 | 1054 | 2016 |
| Data programming: Creating large training sets, quickly AJ Ratner, CM De Sa, S Wu, D Selsam, C Ré Advances in neural information processing systems 29, 2016 | 893 | 2016 |
| Incremental knowledge base construction using DeepDive C De Sa, A Ratner, C Ré, J Shin, F Wang, S Wu, C Zhang The VLDB Journal 26, 81-105, 2017 | 871* | 2017 |
| Hyperbolic graph convolutional neural networks I Chami, Z Ying, C Ré, J Leskovec Advances in neural information processing systems 32, 2019 | 783 | 2019 |
| Probabilistic databases D Suciu, D Olteanu, C Ré, C Koch Springer Nature, 2022 | 684 | 2022 |
| Holoclean: Holistic data repairs with probabilistic inference T Rekatsinas, X Chu, IF Ilyas, C Ré arXiv preprint arXiv:1702.00820, 2017 | 572 | 2017 |
| The MADlib analytics library or MAD skills, the SQL J Hellerstein, C Ré, F Schoppmann, DZ Wang, E Fratkin, A Gorajek, ... arXiv preprint arXiv:1208.4165, 2012 | 549 | 2012 |
| Combining recurrent, convolutional, and continuous-time models with linear state space layers A Gu, I Johnson, K Goel, K Saab, T Dao, A Rudra, C Ré Advances in neural information processing systems 34, 572-585, 2021 | 534 | 2021 |
| Representation tradeoffs for hyperbolic embeddings F Sala, C De Sa, A Gu, C Ré International conference on machine learning, 4460-4469, 2018 | 507 | 2018 |
| Efficient top-k query evaluation on probabilistic data C Re, N Dalvi, D Suciu 2007 IEEE 23rd International Conference on Data Engineering, 886-895, 2006 | 491 | 2006 |
| Hippo: Recurrent memory with optimal polynomial projections A Gu, T Dao, S Ermon, A Rudra, C Ré Advances in neural information processing systems 33, 1474-1487, 2020 | 488 | 2020 |
| Low-dimensional hyperbolic knowledge graph embeddings I Chami, A Wolf, DC Juan, F Sala, S Ravi, C Ré arXiv preprint arXiv:2005.00545, 2020 | 476 | 2020 |
| An asynchronous parallel stochastic coordinate descent algorithm J Liu, S Wright, C Ré, V Bittorf, S Sridhar International Conference on Machine Learning, 469-477, 2014 | 453 | 2014 |
| Worst-case optimal join algorithms HQ Ngo, E Porat, C Ré, A Rudra Journal of the ACM (JACM) 65 (3), 1-40, 2018 | 439 | 2018 |
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