Ziyu Wang

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Jun ZhuProfessor of Computer Science, Tsinghua UniversityVerified email at mail.tsinghua.edu.cn
David WipfPrincipal Research Scientist, Amazon Web ServicesVerified email at amazon.com
Tongzheng RenCitadel SecuritiesVerified email at utexas.edu
Bin Dai清华大学Verified email at mails.tsinghua.edu.cn
Chris HolmesVerified email at stats.ox.ac.uk
Fabian FalckMicrosoft ResearchVerified email at stats.ox.ac.uk
Yuhao ZhouTsinghua UniversityVerified email at mails.tsinghua.edu.cn
Weinan ZhangProfessor, Shanghai Jiao Tong UniversityVerified email at sjtu.edu.cn
Qipeng GuoFudan UniversityVerified email at fudan.edu.cn
Xipeng Qiu（邱锡鹏）Professor of Computer Science, Fudan UniversityVerified email at fudan.edu.cn
Zheng ZhangProfessor of Computer Science and Engineering, NYU Shanghai; Director, Amazon Shanghai AI LabVerified email at nyu.edu
Zhijing JinMax Planck Institute & ETH ZürichVerified email at ethz.ch
Shuyu ChengTsinghua UniversityVerified email at mails.tsinghua.edu.cn
Yucen LuoMax Planck Institute for Intelligent SystemsVerified email at tuebingen.mpg.de
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETHVerified email at tuebingen.mpg.de

Ziyu Wang

Department of Statistics, University of Oxford

Verified email at stats.ox.ac.uk - Homepage

Machine Learning Bayesian Statistics Causal Inference


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The Usual Suspects? Reassessing Blame for VAE Posterior Collapse B Dai, Z Wang, D Wipf International Conference on Machine Learning, 2313-2322, 2020	100	2020
Function Space Particle Optimization for Bayesian Neural Networks Z Wang, T Ren, J Zhu, B Zhang International Conference on Learning Representations, 2019	82	2019
Further Analysis of Outlier Detection with Deep Generative Models Z Wang, B Dai, D Wipf, J Zhu Advances in Neural Information Processing Systems, 8982-8992, 2020	49	2020
Is In-Context Learning in Large Language Models Bayesian? A Martingale Perspective F Falck, Z Wang, C Holmes International Conference on Machine Learning, 2024	16*	2024
Fork or fail: Cycle-consistent training with many-to-one mappings Q Guo, Z Jin, Z Wang, X Qiu, W Zhang, J Zhu, Z Zhang, W David International conference on artificial intelligence and statistics, 1828-1836, 2021	16	2021
Quasi-Bayesian dual instrumental variable regression Z Wang, Y Zhou, T Ren, J Zhu arXiv preprint arXiv:2106.08750, 2021	12*	2021
A Wasserstein Minimum Velocity Approach to Learning Unnormalized Models Z Wang, S Cheng, Y Li, J Zhu, B Zhang International Conference on Artificial Intelligence and Statistics, 3728-3738, 2020	9	2020
Spectral representation learning for conditional moment models Z Wang, Y Luo, Y Li, J Zhu, B Schölkopf arXiv preprint arXiv:2210.16525, 2022	7	2022
Fast Instrument Learning with Faster Rates Z Wang, Y Zhou, J Zhu Advances in Neural Information Processing Systems, 2022	3	2022
On Subjective Uncertainty Quantification and Calibration in Natural Language Generation Z Wang, C Holmes arXiv preprint arXiv:2406.05213, 2024	2	2024
On uncertainty quantification for near-bayes optimal algorithms Z Wang, C Holmes arXiv preprint arXiv:2403.19381, 2024	2	2024
A Constrained Bayesian Approach to Out-of-Distribution Prediction Z Wang, B Yuan, J Lu, B Ding, Y Shao, Q Wu, J Zhu The 39th Conference on Uncertainty in Artificial Intelligence, 2023		2023

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