| Topic modeling in embedding spaces AB Dieng, FJR Ruiz, DM Blei Transactions of the Association for Computational Linguistics 8, 439-453, 2020 | 653 | 2020 |
| Edward: A library for probabilistic modeling, inference, and criticism D Tran, A Kucukelbir, AB Dieng, M Rudolph, D Liang, DM Blei arXiv preprint arXiv:1610.09787, 2016 | 352 | 2016 |
| Topicrnn: A recurrent neural network with long-range semantic dependency AB Dieng, C Wang, J Gao, J Paisley International Conference on Learning Representations (ICLR 2017), 2016 | 277 | 2016 |
| Avoiding Latent Variable Collapse with Generative Skip Models AB Dieng, Y Kim, AM Rush, D Blei Proceedings of the 22 International Conference on Artificial Intelligence …, 2018 | 219 | 2018 |
| Variational Inference via Upper Bound Minimization AB Dieng, D Tran, R Ranganath, J Paisley, D Blei Advances in Neural Information Processing Systems, 2732-2741, 2017 | 179 | 2017 |
| Readmission prediction via deep contextual embedding of clinical concepts C Xiao, T Ma, AB Dieng, DM Blei, F Wang PloS one 13 (4), e0195024, 2018 | 130 | 2018 |
| The dynamic embedded topic model AB Dieng, FJR Ruiz, DM Blei arXiv preprint arXiv:1907.05545, 2019 | 127 | 2019 |
| Prescribed generative adversarial networks AB Dieng, FJR Ruiz, DM Blei, MK Titsias arXiv preprint arXiv:1910.04302, 2019 | 65 | 2019 |
| Consistency regularization for variational auto-encoders S Sinha, AB Dieng Advances in Neural Information Processing Systems 34, 12943-12954, 2021 | 60 | 2021 |
| The vendi score: A diversity evaluation metric for machine learning D Dan Friedman, AB Dieng Transactions on machine learning research, 2023 | 38 | 2023 |
| Augment and Reduce: Stochastic Inference for Large Categorical Distributions FJR Ruiz, MK Titsias, AB Dieng, DM Blei International Conference on Machine Learning, 2018 | 30 | 2018 |
| Noisin: Unbiased Regularization for Recurrent Neural Networks AB Dieng, R Ranganath, J Altosaar, DM Blei Proceedings of the 35th International Conference on Machine Learning (ICML …, 2018 | 28 | 2018 |
| Quantitative nanoinfrared spectroscopy of anisotropic van der Waals materials FL Ruta, AJ Sternbach, AB Dieng, AS McLeod, DN Basov Nano letters 20 (11), 7933-7940, 2020 | 25 | 2020 |
| Reweighted Expectation Maximization AB Dieng, J Paisley arXiv preprint arXiv:1906.05850, 2019 | 19 | 2019 |
| Edward: A library for probabilistic modeling, inference, and criticism, 2016 D Tran, A Kucukelbir, AB Dieng, M Rudolph, D Liang, DM Blei arXiv preprint arXiv:1610.09787, 2016 | 15 | 2016 |
| Llm-prop: Predicting physical and electronic properties of crystalline solids from their text descriptions AN Rubungo, C Arnold, BP Rand, AB Dieng arXiv preprint arXiv:2310.14029, 2023 | 13 | 2023 |
| Markov chain score ascent: A unifying framework of variational inference with Markovian gradients K Kim, J Oh, J Gardner, AB Dieng, H Kim Advances in Neural Information Processing Systems 35, 34802-34816, 2022 | 11 | 2022 |
| Edward: A library for probabilistic modeling, inference, and criticism. arXiv 2016 D Tran, A Kucukelbir, AB Dieng, M Rudolph, D Liang, DM Blei arXiv preprint arXiv:1610.09787, 2016 | 10 | 2016 |
| Vendi sampling for molecular simulations: Diversity as a force for faster convergence and better exploration AP Pasarkar, GM Bencomo, S Olsson, AB Dieng The Journal of chemical physics 159 (14), 2023 | 7 | 2023 |
| DMLR: Data-centric Machine Learning Research--Past, Present and Future L Oala, M Maskey, L Bat-Leah, A Parrish, NM Gürel, TS Kuo, Y Liu, R Dror, ... arXiv preprint arXiv:2311.13028, 2023 | 6 | 2023 |
David BleiProfessor of Statistics and Computer Science, Columbia University在 columbia.edu 的电子邮件经过验证
