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Workshop
Tue 7:30 Philipp Grohs - The Theory-to-Practice Gap in Deep Learning
Philipp Grohs
Spotlight
A Theory-Driven Self-Labeling Refinement Method for Contrastive Representation Learning
Pan Zhou · Caiming Xiong · Xiaotong Yuan · Steven Chu Hong Hoi
Poster
Tue 16:30 A Theory-Driven Self-Labeling Refinement Method for Contrastive Representation Learning
Pan Zhou · Caiming Xiong · Xiaotong Yuan · Steven Chu Hong Hoi
Workshop
Tue 11:00 Q&A Lightning Talks - Challenge Problems and Theory
Cody Coleman · Vijay Janapa Reddi
Workshop
Learning the exchange-correlation functional from nature with differentiable density functional theory
Muhammad Firmansyah Kasim · Sam Vinko
Workshop
Scaling Up Machine Learning For Quantum Field Theory with Equivariant Continuous Flows
Pim de Haan · Roberto Bondesan
Workshop
Probing the Structure of String Theory Vacua with Genetic Algorithms and Reinforcement Learning
Andreas Schachner · Sven Krippendorf · Alex Cole · Gary Shiu
Workshop
Fine-tuning Vision Transformers for the Prediction of State Variables in Ising Models
Onur Kara · Arijit Sehanobish · HECTOR CORZO
Workshop
Mon 11:55 Benefits of using optimal transport in computational learning and inversion
Yunan Yang
Workshop
Mon 6:00 Regularity theory of optimal transport maps
Alessio Figalli
Workshop
Mon 13:00 Keynote: Dorsa Sadigh (Theory and Practice of Partner-Aware Algorithms in Multi-Agent Coordination)
Workshop
Neural quantum states for supersymmetric quantum gauge theories
Enrico Rinaldi