Scholar
RuiKang OuYang
Google Scholar ID: 8G4PuYoAAAAJ
PhD student, University of Cambridge
Sampling Methods
Generative Models
AI4Science
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Citations
33
H-index
3
i10-index
1
Publications
5
Co-authors
11
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Contact
Email
ro352@cam.ac.uk
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Publications
9 items
Controlling Dependence in Implicit Generative Models via Spread Mutual Information
2026
Cited
0
Bridging Stochastic Flow Maps and Boltzmann Generators with Normalizing Flows
2026
Cited
0
Few-Step Boltzmann Generators via Scalable Likelihood Flow Maps
2026
Cited
0
Learning Energy-Based Models from Stochastic Interpolants using Spatiotemporal Differences
2026
Cited
0
Stochastic Interpolants in Hilbert Spaces
2026
Cited
0
A Diffusive Classification Loss for Learning Energy-based Generative Models
2026
Cited
0
Progressive Tempering Sampler with Diffusion
2025
Cited
0
No Trick, No Treat: Pursuits and Challenges Towards Simulation-free Training of Neural Samplers
2025
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0
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Co-authors
10 total
José Miguel Hernández-Lobato
Professor of Machine Learning, University of Cambridge
Jiajun He
PhD Student, University of Cambridge
Bo Qiang
Institute of Protein Design, University of Washington
Shreyas Padhy
University of Cambridge
Yuanqi Du
PhD Student, Cornell University
Dinghuai Zhang 张鼎怀
Microsoft Research; Mila
Wenlin Chen
University of Cambridge, Max Planck Institute for Intelligent Systems
Arno Solin
Associate Professor in Machine Learning, Aalto University
