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 | 59 | 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 | 48 | 2019 |
Meta-learning for stochastic gradient MCMC W Gong, Y Li, JM Hernández-Lobato arXiv preprint arXiv:1806.04522, 2018 | 48 | 2018 |
Sliced kernelized Stein discrepancy W Gong, Y Li, JM Hernández-Lobato arXiv preprint arXiv:2006.16531, 2020 | 41 | 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 | 35 | 2018 |
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 | 28 | 2023 |
Rhino: Deep causal temporal relationship learning with history-dependent noise W Gong, J Jennings, C Zhang, N Pawlowski arXiv preprint arXiv:2210.14706, 2022 | 17 | 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 | 12 | 2022 |
Interpreting diffusion score matching using normalizing flow W Gong, Y Li arXiv preprint arXiv:2107.10072, 2021 | 11 | 2021 |
Active slices for sliced stein discrepancy W Gong, K Zhang, Y Li, JM Hernández-Lobato International Conference on Machine Learning, 3766-3776, 2021 | 6 | 2021 |
Bayesdag: Gradient-based posterior sampling for causal discovery Y Annadani, N Pawlowski, J Jennings, S Bauer, C Zhang, W Gong arXiv preprint arXiv:2307.13917, 2023 | 4 | 2023 |
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 | 3 | 2021 |
Data retrieval S Nowozin, C Zhang, N Koenigstein, C Ma, JMH Lobato, G Wenbo US Patent App. 16/357,321, 2020 | 3 | 2020 |
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 | 2 | 2024 |
The Essential Role of Causality in Foundation World Models for Embodied AI T Gupta, W Gong, C Ma, N Pawlowski, A Hilmkil, M Scetbon, A Famoti, ... arXiv preprint arXiv:2402.06665, 2024 | 2 | 2024 |
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 |
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 | 1 | 2022 |
Advances in approximate inference: combining VI and MCMC and improving on Stein discrepancy W Gong | 1 | 2022 |
Modelling causation in machine learning G Wenbo, C Zhang, N Pawlowski, J Jennings, K Fassio, M Defante, ... US Patent App. 17/936,347, 2024 | | 2024 |
Collecting observations for machine learning C Zhang, G Wenbo, RE Turner, S Tschiatschek, JMH LOBATO US Patent App. 18/450,365, 2023 | | 2023 |