Wenbo Gong

Affiliations:
  • University of Cambridge, Cambridge, UK


According to our database1, Wenbo Gong authored at least 17 papers between 2019 and 2024.

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Bibliography

2024
Deep End-to-end Causal Inference.
Trans. Mach. Learn. Res., 2024

The Essential Role of Causality in Foundation World Models for Embodied AI.
CoRR, 2024

Neural structure learning with stochastic differential equations.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
BayesDAG: Gradient-Based Posterior Sampling for Causal Discovery.
CoRR, 2023

Understanding Causality with Large Language Models: Feasibility and Opportunities.
CoRR, 2023

BayesDAG: Gradient-Based Posterior Inference for Causal Discovery.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Rhino: Deep Causal Temporal Relationship Learning with History-dependent Noise.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Instructions and Guide: Causal Insights for Learning Paths in Education.
CoRR, 2022

Deep End-to-end Causal Inference.
CoRR, 2022

Simultaneous Missing Value Imputation and Structure Learning with Groups.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Advances in approximate inference: combining VI and MCMC and improving on Stein discrepancy.
PhD thesis, 2021

Interpreting diffusion score matching using normalizing flow.
CoRR, 2021

Active Slices for Sliced Stein Discrepancy.
Proceedings of the 38th International Conference on Machine Learning, 2021

Sliced Kernelized Stein Discrepancy.
Proceedings of the 9th International Conference on Learning Representations, 2021

2019
Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model.
CoRR, 2019

Icebreaker: Element-wise Efficient Information Acquisition with a Bayesian Deep Latent Gaussian Model.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Meta-Learning For Stochastic Gradient MCMC.
Proceedings of the 7th International Conference on Learning Representations, 2019


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