Yilun Xu
Reserach Scientist at Meta
Cambridge, Massachusetts, United States
Summary
👤
Senior🎓
Top SchoolYilun Xu is a research scientist with eight years of experience advancing generative modeling and diffusion techniques across industry and academia. He completed a PhD-level trajectory at MIT and moved from influential academic work at Stanford (ICLR oral and follow-ups) into research roles at NVIDIA, Google DeepMind (Gemini team), and now Meta. At NVIDIA he co-led diffusion distillation efforts such as COSMOS NANO, and at DeepMind worked on generative models that simulate the world. His work bridges theoretical contributions (V-information, anytime sampling) with practical model distillation and large-scale generative systems. Based in Cambridge, MA, he combines deep probabilistic modeling expertise with hands-on engineering to push sampled-based methods toward production. Colleagues know him for pairing rigorous research results with reproducible code and pragmatic distillation strategies that speed up deployment.
8 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD, EECS, Doctor of Philosophy - PhD, EECS at Massachusetts Institute of TechnologyBachelor's degree, Computer Science, Bachelor's degree, Computer Science at Peking University
Github Skills (59)
poisson10
variational-autoencoder10
generative-adversarial-network10
generative10
density-estimation10
loss9
dmi8
noise8
deep-learning8
audio8
flux8
pytorch8
text-to-image7
survey7
multi-task-learning7
Programming languages (2)
Github contributions (5)
Newbeeer/Poisson_flow
Oct 2022 - Jan 2023
Code for NeurIPS 2022 Paper, "Poisson Flow Generative Models" (PFGM)
Contributions:68 commits, 108 pushes, 1 branch in 2 months
pytorchdeep-learningneuripsdensity-estimationpoisson
Newbeeer/Max-MIG
Jun 2019 - Jun 2023
Contributions:10 pushes, 1 branch, 4 comments in 3 years 11 months
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