Yule Wang’s Personal Homepage

I am a second-year PhD student in the Machine Learning Program and the CSE Department at Georgia Tech, advised by Prof. Anqi Wu. My current research interest lies in Probabilistic Machine Learning with its applications in Computational Neuroscience. More specifically, the modeling topics of my research span on: Diffusion (Probabilistic) Models, Variational Autoencoder, Bayesian inference, and Importance Sampling. I received my Master’s and Bachelor’s degree from Shanghai Jiao Tong University majoring in Computer Software Engineering.

Please drop me an email if you’d like to chat or collaborate!

Recent Updates

• [May. 2024] Two papers “Multi-Region Markovian Gaussian Process: An Efficient Method to Discover Directional Communications Across Multiple Brain Regions” and “A Differentiable POGLM with Forward-Backward Message Passing” are accepted to ICML 2024 as posters!
• [Jan. 2024] Our paper “Forward $\chi^2$ Divergence Based Variational Importance Sampling” is accepted to ICLR 2024 as a spotlight (top 3%)!
• [Jan. 2024] The abstract of our paper “Extraction and Recovery of Spatio-Temporal Structure in Latent Dynamics Alignment with Diffusion Models” is also accepted to COSYNE 2024! See you in Lisbon!
• [Sep. 2023] Our paper “Extraction and Recovery of Spatio-Temporal Structure in Latent Dynamics Alignment with Diffusion Models” is accepted to NeurIPS 2023 as a spotlight (top 3%)! See you in New Orleans!

Academic Services

Conference Reviewer: ICML’23, NeurIPS’23, ICLR’24, ICML’24, NeurIPS’24

Contact Information

• My email address is yulewang AT gatech DOT edu