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ORCIDWenbo Gong 0001
Person information
- affiliation: University of Cambridge, Cambridge, UK
Other persons with the same name
- Wenbo Gong 0002 — China University of Mining and Technology, Beijing, China
- Wenbo Gong 0003 — University of Science and Technology, Beijing, China
- Wenbo Gong 0004 — Guilin University of Electronic Technology, Guilin, Guangxi, China
- Wenbo Gong 0005 — Harbin Institute of Technology, School of Science, Shenzhen, China
- Wenbo Gong 0006 — Shaanxi Tongwei Digital Technology Company Ltd., Xi'an, China
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2020 – today
- 2024
[j1]Tomas Geffner, Javier Antorán, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Nick Pawlowski, Agrin Hilmkil, Joel Jennings, Meyer Scetbon, Miltiadis Allamanis, Cheng Zhang:
Deep End-to-end Causal Inference. Trans. Mach. Learn. Res. 2024 (2024)- [c8]Benjie Wang, Joel Jennings, Wenbo Gong:
Neural structure learning with stochastic differential equations. ICLR 2024 - [i12]Tarun Gupta, Wenbo Gong, Chao Ma, Nick Pawlowski, Agrin Hilmkil, Meyer Scetbon, Ade Famoti, Ashley Juan Llorens, Jianfeng Gao, Stefan Bauer, Danica Kragic, Bernhard Schölkopf, Cheng Zhang:
The Essential Role of Causality in Foundation World Models for Embodied AI. CoRR abs/2402.06665 (2024) - 2023
- [c7]Wenbo Gong, Joel Jennings, Cheng Zhang, Nick Pawlowski:
Rhino: Deep Causal Temporal Relationship Learning with History-dependent Noise. ICLR 2023 - [c6]Yashas Annadani, Nick Pawlowski, Joel Jennings, Stefan Bauer, Cheng Zhang, Wenbo Gong:
BayesDAG: Gradient-Based Posterior Inference for Causal Discovery. NeurIPS 2023 - [i11]Cheng Zhang, Stefan Bauer, Paul Bennett, Jiangfeng Gao, Wenbo Gong, Agrin Hilmkil, Joel Jennings, Chao Ma, Tom Minka, Nick Pawlowski, James Vaughan:
Understanding Causality with Large Language Models: Feasibility and Opportunities. CoRR abs/2304.05524 (2023) - [i10]Yashas Annadani, Nick Pawlowski, Joel Jennings, Stefan Bauer, Cheng Zhang, Wenbo Gong:
BayesDAG: Gradient-Based Posterior Sampling for Causal Discovery. CoRR abs/2307.13917 (2023) - [i9]Benjie Wang, Joel Jennings, Wenbo Gong:
Neural Structure Learning with Stochastic Differential Equations. CoRR abs/2311.03309 (2023) - 2022
- [c5]Pablo Morales-Alvarez, Wenbo Gong, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang:
Simultaneous Missing Value Imputation and Structure Learning with Groups. NeurIPS 2022 - [i8]Tomas Geffner, Javier Antorán, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang:
Deep End-to-end Causal Inference. CoRR abs/2202.02195 (2022) - [i7]Wenbo Gong, Digory Smith, Zichao Wang, Craig Barton, Simon Woodhead, Nick Pawlowski, Joel Jennings, Cheng Zhang:
Instructions and Guide: Causal Insights for Learning Paths in Education. CoRR abs/2208.12610 (2022) - [i6]Wenbo Gong, Joel Jennings, Cheng Zhang, Nick Pawlowski:
Rhino: Deep Causal Temporal Relationship Learning With History-dependent Noise. CoRR abs/2210.14706 (2022) - 2021
- [b1]Wenbo Gong:
Advances in approximate inference: combining VI and MCMC and improving on Stein discrepancy. University of Cambridge, UK, 2021 - [c4]Wenbo Gong, Yingzhen Li, José Miguel Hernández-Lobato:
Sliced Kernelized Stein Discrepancy. ICLR 2021 - [c3]Wenbo Gong, Kaibo Zhang, Yingzhen Li, José Miguel Hernández-Lobato:
Active Slices for Sliced Stein Discrepancy. ICML 2021: 3766-3776 - [i5]Wenbo Gong, Kaibo Zhang, Yingzhen Li, José Miguel Hernández-Lobato:
Active Slices for Sliced Stein Discrepancy. CoRR abs/2102.03159 (2021) - [i4]Wenbo Gong, Yingzhen Li:
Interpreting diffusion score matching using normalizing flow. CoRR abs/2107.10072 (2021) - 2020
- [i3]Wenbo Gong, Yingzhen Li, José Miguel Hernández-Lobato:
Sliced Kernelized Stein Discrepancy. CoRR abs/2006.16531 (2020)
2010 – 2019
- 2019
- [c2]Wenbo Gong, Yingzhen Li, José Miguel Hernández-Lobato:
Meta-Learning For Stochastic Gradient MCMC. ICLR (Poster) 2019 - [c1]Wenbo Gong, Sebastian Tschiatschek, Sebastian Nowozin, Richard E. Turner, José Miguel Hernández-Lobato, Cheng Zhang:
Icebreaker: Element-wise Efficient Information Acquisition with a Bayesian Deep Latent Gaussian Model. NeurIPS 2019: 14791-14802 - [i2]Wenbo Gong, Sebastian Tschiatschek, Richard E. Turner, Sebastian Nowozin, José Miguel Hernández-Lobato, Cheng Zhang:
Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model. CoRR abs/1908.04537 (2019) - 2018
- [i1]Wenbo Gong, Yingzhen Li, José Miguel Hernández-Lobato:
Meta-Learning for Stochastic Gradient MCMC. CoRR abs/1806.04522 (2018)
Coauthor Index
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