Yanbo Wang

I'm a PhD Candidate at TU Delft in the Netherlands, supervised by Prof. Justin Dauwels and Prof. Geert Leus. I received my master's degree from George Mason University in the U.S., honored with Outstanding Academic Achievement Award. I was a Best Student Paper Finalist at Asilomar 2020.

Email  /  Scholar  /  Github

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Research

I am interested in generative models, object-centric learning, and compositional modeling, with focus on generalization to novel settings beyond training data. The applications include visual content generation, scene understanding, physical reasoning, and robotic manipulation.

News

  • 2025.05    Paper "Compositional Scene Understanding through Inverse Generative Modeling" accepted by ICML 2025.
  • 2025.01    I will be joining Qualcomm AI Research Amsterdam as a Research Scientist Intern in the summer of 2025.
  • 2024.05    I give a talk on "Compositional Generative Models" at ASML, the Netherlands.
  • 2024.04    Paper "Compositional Image Decomposition with Diffusion Models" accepted by ICML 2024.

Selected Publications (* stands for equal contribution)

b3do Compositional Scene Understanding through Inverse Generative Modeling
Yanbo Wang, Justin Dauwels, Yilun Du
ICML, 2025
Website / Paper / Code
b3do Compositional Image Decomposition with Diffusion Models
Jocelin Su*, Nan Liu*, Yanbo Wang*, Joshua B. Tenenbaum, Yilun Du
ICML, 2024
Website / Paper / Code
b3do Slot-VAE: Object-Centric Compositional Image Generation with Slot Attention
Yanbo Wang, Letao Liu, Justin Dauwels,
ICML, 2023
Website / Paper / Code

Miscellanea

Research Talks

Compositional Inference for Generalizing beyond Training Distribution, SPS Seminar, TU Delft, 2025.
Composing EBMs and Diffusion Models, ASML, Eindhoven, 2024.
Object-Centric Image Generation with Hierarchical VAE, SPS Seminar, TU Delft, 2024

Academic Service

Reviewer, ICLR 2025
Reviewer, ICML 2025
Reviewer, NeurIPS 2025

Teaching Experience

Co-instructor, EE4685 Machine Learning, a Bayesian Perspective (Graduate), 2023-2024
Co-instructor, EE4C12 Machine Learning for Electrical Engineering (Graduate), 2022-2024

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