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Progressive Tempering Sampler with Diffusion Sampling Diffusion AI for Science
Severi Rissanen*, RuiKang OuYang*, Jiajun He, Wenlin Chen, Markus Heinonen, Arno Solin, José Miguel Hernández-Lobato
ICML 2025
PDF Cite Code arXiv
Training Neural Samplers with Reverse Diffusive KL Divergence Sampling Diffusion AI for Science
Jiajun He*, Wenlin Chen*, Mingtian Zhang*, David Barber, José Miguel Hernández-Lobato
AISTATS 2025
PDF Cite Code PMLR arXiv
Neural Characteristic Activation Analysis and Geometric Parameterization for ReLU Networks Optimization
Wenlin Chen, Hong Ge
NeurIPS 2024
PDF Cite Code NeurIPS Proceedings arXiv
Modelling Variability in Human Annotator Simulation Uncertainty
Wen Wu*, Wenlin Chen*, Chao Zhang, Phil Woodland
ACL 2024
PDF Cite Code ACL Anthology arXiv
Diffusive Gibbs Sampling Sampling Diffusion AI for Science
Wenlin Chen*, Mingtian Zhang*, Brooks Paige, José Miguel Hernández-Lobato, David Barber
ICML 2024
PDF Cite Code PMLR arXiv
Meta-learning Adaptive Deep Kernel Gaussian Processes for Molecular Property Prediction Multi-Task Uncertainty AI for Science
Wenlin Chen, Austin Tripp, José Miguel Hernández-Lobato
ICLR 2023
PDF Cite Code OpenReview arXiv
To Ensemble or Not Ensemble: When Does End-to-End Training Fail? Optimization
Andrew Webb, Charles Reynolds, Wenlin Chen, Henry Reeve, Dan Iliescu, Mikel Luján, Gavin Brown
ECML 2020
PDF Cite Code Video Springer arXiv