Yule Wang

yule-profile-avatar.png

CODA 1349R

756 W Peachtree St NW

Atlanta, GA 30308

School of CSE, Georgia Institute of Technology

Email: yulewang [at] gatech [dot] edu

I am a third-year Ph.D. student in the Machine Learning Program and the CSE Department at Georgia Tech (GaTech). My advisor is Prof. Anqi Wu. I obtained my Master’s and B.Eng.’s degree from Shanghai Jiao Tong University majoring in Computer Software Engineering. I also spent time as a research intern at ByteDance and Alibaba.

Research Topics

My Research Interest lies in probabilistic machine learning, with its applications in computational neuroscience. More specifically, my ML research focuses on the intersection of (deep) generative models and sequence modeling. Working with multivariate time-series data, I develop ML algorithms to infer semantically or scientifically meaningful latent structures and dynamics through advanced generative modeling approaches (e.g., disentangled variational auto-encoder, video diffusion models).

I am open to collaborate💡! Feel free to drop me an email if you are interested!

News

Oct 15, 2024 I am honored to receive the NeurIPS 2024 Scholar Award. Looking forward to seeing you in Vancouver, Canada!

Selected Publications

  1. NeurIPS
    Exploring Behavior-Relevant and Disentangled Neural Dynamics with Generative Diffusion Models
    Yule Wang, Chengrui Li, Weihan Li, and Anqi Wu
    Advances in Neural Information Processing Systems, 2024
  2. ICLR
    Forward χ^2 Divergence Based Variational Importance Sampling
    Chengrui Li, Yule Wang, Weihan Li, and Anqi Wu
    International Conference on Learning Representations Spotlight, 2024
  3. NeurIPS
    Extraction and Recovery of Spatio-Temporal Structure in Latent Dynamics Alignment with Diffusion Models
    Yule Wang, Zijing Wu, Chengrui Li, and Anqi Wu
    Advances in Neural Information Processing Systems Spotlight, 2023