Max Welling

University of California, Santa Barbara — United States

Computer Science · Physical Sciences

87h-index83.0kcitations522works500.02yr avg
OpenAlex↗ORCID↗Google Scholar↗Lab page↗

Accepting Students?

No reports yet. Know if this professor is taking students?

Research Topics

Gaussian Processes and Bayesian Inference(82), Neural Networks and Applications(71), Generative Adversarial Networks and Image Synthesis(68), Bayesian Methods and Mixture Models(60), Domain Adaptation and Few-Shot Learning(45)

Publications521 total

Accelerating scientific discovery with the common task framework
arXiv (Cornell University)·2025Open Access
Learned free-energy functionals from pair-correlation matching for dynamical density functional theory
Physical review. E·2025Open Access
Purrception: Variational Flow Matching for Vector-Quantized Image Generation
arXiv (Cornell University)·2025Open Access
Kuramoto Orientation Diffusion Models
arXiv (Cornell University)·2025Open Access
BLIPs: Bayesian Learned Interatomic Potentials
arXiv (Cornell University)·2025Open Access
Langevin Flows for Modeling Neural Latent Dynamics
arXiv (Cornell University)·2025Open Access
Controlled Generation with Equivariant Variational Flow Matching
arXiv (Cornell University)·2025Open Access
A foundation model for the Earth system
Nature·2025· 75 citedOpen Access
Flow Factorized Representation Learning
Synthesis lectures on computer vision·2025
Introduction
Synthesis lectures on computer vision·2025
Unsupervised Factorized Representation Learning Based on Sparse Transformation Analysis
Synthesis lectures on computer vision·2025
Conclusion
Synthesis lectures on computer vision·2025
Background
Synthesis lectures on computer vision·2025
Structured Representation Learning
Synthesis lectures on computer vision·2025
Topographic Variational Autoencoders
Synthesis lectures on computer vision·2025· 1 cited
Neural Wave Machines
Synthesis lectures on computer vision·2025
Latent Traversal as Potential Flows
Synthesis lectures on computer vision·2025
Learned Free-Energy Functionals from Pair-Correlation Matching for Dynamical Density Functional Theory
arXiv (Cornell University)·2025Open Access
Erwin: A Tree-based Hierarchical Transformer for Large-scale Physical Systems
arXiv (Cornell University)·2025Open Access
Learning Neural Free-Energy Functionals with Pair-Correlation Matching
Physical Review Letters·2025· 13 cited
page 1 of 27Next →

Frequent Co-authors

Diederik P. Kingma(9), Thomas Kipf(8), Taco Cohen(6), Christos Louizos(5), Richard S. Zemel(5), Tim Salimans(4), David Newman(4), Arthur Asuncion(4), Padhraic Smyth(4), Yee Whye Teh(3), Zoubin Ghahramani(3), Kilian Q. Weinberger(3), Bastian Leibe(3), Jiřı́ Matas(3), Nicu Sebe(3), Rianne van den Berg(2), Rafał Józefowicz(2), Xi Chen(2), Ilya Sutskever(2), Corinna Cortes(2)