One world theoretical machine learning
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One world theoretical machine learning
10 posts · theirs
Lately
Alex Damian - Understanding Optimization in Deep Learning with Central Flows
Minshuo Chen - Unlocking Adaptive Generative Decision-Making with Diffusion Models
Tizian Wenzel: On the optimal shape parameter for kernel methods and beyond
Nicolas Boffi - Flow map language models
Xiong Wang: Statistical learning problems in interacting particle systems
Giulio Biroli - Why Diffusion Models Don't Memorize
Pierre-Alexandre Mattei - Ensembles in machine learning: (simple) theory and (simple) practice
Yingzhen Li - Variational Uncertainty Decomposition for In-Context Learning
Qing Qu - Understanding Generalization of Deep Generative Models based on Low-dimensional Structures
Andrew Ilersich - Learning Stochastic Multiscale Models of Spatiotemporal Systems
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