Zuheng Xu

According to our database, Zuheng Xu authored at least 15 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Tuning Sequential Monte Carlo Samplers via Greedy Incremental Divergence Minimization.

Kyurae Kim, Zuheng Xu, Jacob R. Gardner, Trevor Campbell

CoRR, March, 2025

Recent Advances, Applications and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2024 Symposium.

Amin Adibi, Xu Cao, Zongliang Ji, Jivat Neet Kaur, Winston Chen, Elizabeth Healey, Brighton Nuwagira, Wenqian Ye, Geoffrey Woollard, Maxwell A. Xu, Hejie Cui, Johnny Xi, Trenton Chang, Vasiliki Bikia, Nicole Zhang, Ayush Noori, Yuan Xia, Md. Belal Hossain, Hanna A. Frank, Alina Peluso, Yuan Pu, Shannon Zejiang Shen, John Wu, Adibvafa Fallahpour, Sazan Mahbub, Ross Duncan, Yuwei Zhang, Yurui Cao, Zuheng Xu, Michael Craig, Rahul G. Krishnan, Rahmatollah Beheshti, James M. Rehg, Mohammad Ehsanul Karim, Megan Coffee, Leo Anthony Celi, Jason Alan Fries, Mohsen Sadatsafavi, Dennis L. Shung, Shannon K. McWeeney, Jessica Dafflon, Sarah Jabbour

CoRR, February, 2025

Is Gibbs sampling faster than Hamiltonian Monte Carlo on GLMs?

Son Luu, Zuheng Xu, Nikola Surjanovic, Miguel Biron-Lattes, Trevor Campbell, Alexandre Bouchard-Côté

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

Automated Discovery of Pairwise Interactions from Unstructured Data.

Zuheng Xu, Moksh Jain, Ali Denton, Shawn Whitfield, Aniket Didolkar, Berton Earnshaw, Jason S. Hartford

CoRR, 2024

Propensity Score Alignment of Unpaired Multimodal Data.

Johnny Xi, Jana Osea, Zuheng Xu, Jason S. Hartford

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Turning Waste into Wealth: Leveraging Low-Quality Samples for Enhancing Continuous Conditional Generative Adversarial Networks.

Xin Ding, Yongwei Wang, Zuheng Xu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Continuous Conditional Generative Adversarial Networks: Novel Empirical Losses and Label Input Mechanisms.

Xin Ding, Yongwei Wang, Zuheng Xu, William J. Welch, Z. Jane Wang

IEEE Trans. Pattern Anal. Mach. Intell., July, 2023

Distilling and transferring knowledge via cGAN-generated samples for image classification and regression.

Xin Ding, Yongwei Wang, Zuheng Xu, Z. Jane Wang, William J. Welch

Expert Syst. Appl., March, 2023

Embracing the chaos: analysis and diagnosis of numerical instability in variational flows.

Zuheng Xu, Trevor Campbell

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

MixFlows: principled variational inference via mixed flows.

Zuheng Xu, Naitong Chen, Trevor Campbell

Proceedings of the International Conference on Machine Learning, 2023

2022

The computational asymptotics of Gaussian variational inference and the Laplace approximation.

Zuheng Xu, Trevor Campbell

Stat. Comput., 2022

Ergodic variational flows.

Zuheng Xu, Naitong Chen, Trevor Campbell

CoRR, 2022

Bayesian inference via sparse Hamiltonian flows.

Naitong Chen, Zuheng Xu, Trevor Campbell

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

CcGAN: Continuous Conditional Generative Adversarial Networks for Image Generation.

Xin Ding, Yongwei Wang, Zuheng Xu, William J. Welch, Z. Jane Wang

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Bayesian Pseudocoresets.

Dionysis Manousakas, Zuheng Xu, Cecilia Mascolo, Trevor Campbell

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020