| Streaming variational bayes T Broderick, N Boyd, A Wibisono, AC Wilson, MI Jordan Advances in neural information processing systems 26, 2013 | 402 | 2013 |
| Transparency and reproducibility in artificial intelligence B Haibe-Kains, GA Adam, A Hosny, F Khodakarami, ... Nature 586 (7829), E14-E16, 2020 | 398 | 2020 |
| Coresets for scalable Bayesian logistic regression J Huggins, T Campbell, T Broderick Advances in neural information processing systems 29, 2016 | 265 | 2016 |
| Diffusion probabilistic modeling of protein backbones in 3d for the motif-scaffolding problem BL Trippe, J Yim, D Tischer, D Baker, T Broderick, R Barzilay, T Jaakkola arXiv preprint arXiv:2206.04119, 2022 | 221 | 2022 |
| Bayesian coreset construction via greedy iterative geodesic ascent T Campbell, T Broderick International Conference on Machine Learning, 698-706, 2018 | 150 | 2018 |
| Ellipticity of dark matter haloes with galaxy–galaxy weak lensing R Mandelbaum, CM Hirata, T Broderick, U Seljak, J Brinkmann Monthly Notices of the Royal Astronomical Society 370 (2), 1008-1024, 2006 | 144 | 2006 |
| Covariances, robustness, and variational Bayes R Giordano, T Broderick, MI Jordan Journal of machine learning research 19 (51), 1-49, 2018 | 138 | 2018 |
| Automated scalable Bayesian inference via Hilbert coresets T Campbell, T Broderick Journal of Machine Learning Research 20 (15), 1-38, 2019 | 132 | 2019 |
| A swiss army infinitesimal jackknife R Giordano, W Stephenson, R Liu, M Jordan, T Broderick The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 119 | 2019 |
| Beta processes, stick-breaking and power laws T Broderick, MI Jordan, J Pitman | 117 | 2012 |
| Linear response methods for accurate covariance estimates from mean field variational Bayes RJ Giordano, T Broderick, MI Jordan Advances in neural information processing systems 28, 2015 | 108 | 2015 |
| MAD-Bayes: MAP-based asymptotic derivations from Bayes T Broderick, B Kulis, M Jordan International Conference on Machine Learning, 226-234, 2013 | 103 | 2013 |
| Edge-exchangeable graphs and sparsity D Cai, T Campbell, T Broderick Advances in Neural Information Processing Systems 29, 2016 | 97 | 2016 |
| Combinatorial clustering and the beta negative binomial process T Broderick, L Mackey, J Paisley, MI Jordan IEEE transactions on pattern analysis and machine intelligence 37 (2), 290-306, 2014 | 88 | 2014 |
| Feature allocations, probability functions, and paintboxes T Broderick, J Pitman, MI Jordan | 85 | 2013 |
| Boosting variational inference F Guo, X Wang, K Fan, T Broderick, DB Dunson arXiv preprint arXiv:1611.05559, 2016 | 84 | 2016 |
| Faster solutions of the inverse pairwise Ising problem T Broderick, M Dudik, G Tkacik, RE Schapire, W Bialek arXiv preprint arXiv:0712.2437, 2007 | 84 | 2007 |
| Faster solutions of the inverse pairwise Ising problem T Broderick, M Dudik, G Tkacik, RE Schapire, W Bialek arXiv preprint arXiv:0712.2437, 2007 | 84 | 2007 |
| Validated variational inference via practical posterior error bounds J Huggins, M Kasprzak, T Campbell, T Broderick International Conference on Artificial Intelligence and Statistics, 1792-1802, 2020 | 67* | 2020 |
| Redshift accuracy requirements for future supernova and number count surveys D Huterer, A Kim, LM Krauss, T Broderick The Astrophysical Journal 615 (2), 595, 2004 | 53 | 2004 |
