| Deep end-to-end causal inference T Geffner, J Antoran, A Foster, W Gong, C Ma, E Kiciman, A Sharma, ... arXiv preprint arXiv:2202.02195, 2022 | 83 | 2022 |
| Icebreaker: Element-wise efficient information acquisition with a bayesian deep latent gaussian model W Gong, S Tschiatschek, S Nowozin, RE Turner, JM Hernández-Lobato, ... Advances in neural information processing systems 32, 2019 | 58 | 2019 |
| Understanding causality with large language models: Feasibility and opportunities C Zhang, S Bauer, P Bennett, J Gao, W Gong, A Hilmkil, J Jennings, C Ma, ... arXiv preprint arXiv:2304.05524, 2023 | 55 | 2023 |
| Meta-learning for stochastic gradient MCMC W Gong, Y Li, JM Hernández-Lobato arXiv preprint arXiv:1806.04522, 2018 | 52 | 2018 |
| Sliced kernelized Stein discrepancy W Gong, Y Li, JM Hernández-Lobato arXiv preprint arXiv:2006.16531, 2020 | 45 | 2020 |
| Partial VAE for hybrid recommender system C Ma, W Gong, JM Hernández-Lobato, N Koenigstein, S Nowozin, ... NIPS Workshop on Bayesian Deep Learning 2018, 2018 | 43 | 2018 |
| Rhino: Deep causal temporal relationship learning with history-dependent noise W Gong, J Jennings, C Zhang, N Pawlowski arXiv preprint arXiv:2210.14706, 2022 | 33 | 2022 |
| Simultaneous missing value imputation and structure learning with groups P Morales-Alvarez, W Gong, A Lamb, S Woodhead, S Peyton Jones, ... Advances in Neural Information Processing Systems 35, 20011-20024, 2022 | 20 | 2022 |
| BayesDAG: gradient-based posterior inference for causal discovery Y Annadani, N Pawlowski, J Jennings, S Bauer, C Zhang, W Gong Advances in Neural Information Processing Systems 36, 2024 | 18 | 2024 |
| Interpreting diffusion score matching using normalizing flow W Gong, Y Li arXiv preprint arXiv:2107.10072, 2021 | 14 | 2021 |
| The essential role of causality in foundation world models for embodied ai T Gupta, W Gong, C Ma, N Pawlowski, A Hilmkil, M Scetbon, M Rigter, ... arXiv preprint arXiv:2402.06665, 2024 | 10 | 2024 |
| Bayesdag: Gradient-based posterior sampling for causal discovery Y Annadani, N Pawlowski, J Jennings, S Bauer, C Zhang, W Gong ICML 2023 Workshop on Structured Probabilistic Inference {\&} Generative …, 2023 | 8 | 2023 |
| Active slices for sliced Stein discrepancy W Gong, K Zhang, Y Li, JM Hernández-Lobato International Conference on Machine Learning, 3766-3776, 2021 | 7 | 2021 |
| Data retrieval S Nowozin, C Zhang, N Koenigstein, C Ma, JMH Lobato, G Wenbo US Patent App. 16/357,321, 2020 | 7 | 2020 |
| Vicause: Simultaneous missing value imputation and causal discovery with groups P Morales-Alvarez, A Lamb, S Woodhead, SP Jones, M Allamanis, ... arXiv preprint arXiv 2110, 2021 | 4 | 2021 |
| Advances in approximate inference: combining VI and MCMC and improving on Stein discrepancy W Gong | 3 | 2022 |
| Neural structure learning with stochastic differential equations B Wang, J Jennings, W Gong arXiv preprint arXiv:2311.03309, 2023 | 2 | 2023 |
| NeurIPS competition instructions and guide: Causal insights for learning paths in education W Gong, D Smith, Z Wang, C Barton, S Woodhead, N Pawlowski, ... arXiv preprint arXiv:2208.12610, 2022 | 2 | 2022 |
| Instructions and guide: Causal insights for learning paths in education W Gong, D Smith, Z Wang, C Barton, S Woodhead, N Pawlowski, ... arXiv preprint arXiv:2208.12610, 2022 | 2 | 2022 |
| CausalEdu: a real-world education dataset for temporal causal discovery and inference W Gong, D Smith, Z Wang, C Barton, S Woodhead, N Pawlowski, ... | 1 | 2023 |
