Topics in Deep Learning Theory
CMSA Room G10 CMSA, 20 Garden Street, Cambridge, MA, United StatesTopics in Deep Learning Theory Eli Grigsby
Topics in Deep Learning Theory Eli Grigsby
Open Discussion/Tea
Geometry and Quantum Theory Seminar Speaker: Vasily Krylov, Harvard CMSA & Math Title: Symplectic duality in examples Abstract: Over the past twenty years, mathematicians and physicists have shown increasing interest […]
Math and Machine Learning Program Discussion
https://youtu.be/0998FJhPdj8 New Technologies in Mathematics Seminar Speaker: Blake Bordelon Title: Infinite Limits and Scaling Laws for Deep Neural Networks Abstract: Scaling up the size and training horizon of deep learning models has enabled […]
Mathematical Physics and Algebraic Geometry Speaker: Junrong Yan (Northeastern University) Title: Witten deformation for non-Morse functions and gluing formulas Abstract: Witten deformation is a versatile tool with numerous applications in […]
Topics in Deep Learning Theory Eli Grigsby
Quantum Field Theory and Physical Mathematics Speaker: Sergei Gukov (Caltech) Title: Going to the other side .... in algebra, topology, and maybe physics Abstract: Inspired by Eugene Wigner's reflections on […]
Math and Machine Learning Program Discussion
Math and Machine Learning Program Discussion
https://youtu.be/Pht8aXE5IsU Machine Learning in Science Education Panel Discussion Monday, Sep. 30, 2024 3:30-5:30 pm ET Machine Learning is rapidly influencing many spheres of human activity. As part of the CMSA […]
General Relativity Seminar Speaker: Daniel Kapec, Harvard Title: Quasinormal Corrections to Near-Extremal Black Hole Thermodynamics Abstract: Recent work on the quantum mechanics of near-extremal non-supersymmetric black holes has identified a […]