Structured Disentangled Representations B Esmaeili, H Wu, S Jain, A Bozkurt, N Siddharth, B Paige, DH Brooks, ... The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 204* | 2019 |
Nested Variational Inference H Zimmermann, H Wu, B Esmaeili, S Stites, JW van de Meent Proceedings of the 35th Conference on Neural Information Processing Systems, 2021 | 23 | 2021 |
Learning Proposals for Probabilistic Programs with Inference Combinators S Stites, H Zimmermann, H Wu, E Sennesh, JW van de Meent Proceedings of the 37th Conference on Uncertainty in Artificial Intelligence, 2021 | 13 | 2021 |
Conjugate Energy-Based Models H Wu, B Esmaeili, M Wick, JB Tristan, JW van de Meent Proceedings of the 38th International Conference on Machine Learning, 2021 | 7 | 2021 |
Amortized Population Gibbs Samplers with Neural Sufficient Statistics H Wu, H Zimmermann, E Sennesh, TA Le, JW Van De Meent Proceedings of the 37th International Conference on Machine Learning 119 …, 2020 | 7 | 2020 |
Gradient-free variational learning with conditional mixture networks C Heins, H Wu, D Markovic, A Tschantz, J Beck, C Buckley NeurIPS 2024 Workshop on Bayesian Decision-making and Uncertainty, 2024 | 1 | 2024 |
Divide-and-Conquer Predictive Coding: a structured Bayesian inference algorithm E Sennesh, H Wu, T Salvatori Proceedings of the 38th Conference on Neural Information Processing Systems, 2024 | 1 | 2024 |
Composing Modeling and Inference Operations with Probabilistic Program Combinators E Sennesh, A Ścibior, H Wu, JW van de Meent NeurIPS 2018 Workshop on Bayesian Nonparametrics, 2018 | | 2018 |