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
Geometry and Quantum Theory Seminar Speaker: Mayuko Yamashita, Kyoto University Title: Topological Modular Forms, its equivariant refinements and relation with supersymmetric quantum field theories Abstract: This talk is about the […]
Math and Machine Learning Program Discussion
CMSA Q&A Seminar Speaker: Nazim Bouatta (HMS) Topic: What are AlphaFold2 and OpenFold
https://youtu.be/OYOuSAAE7QQ New Technologies in Mathematics Seminar Speaker: Anirudh Goyal (University of Montreal) Title: From Word Prediction to Complex Skills: Data Flywheels for Mathematical Reasoning Abstract: This talk examines how large language models […]
Speaker: Andrew Neitzke, Yale University Location: Harvard University Science Center Hall D & via Zoom webinar Dates: October 16 & 17, 2024 Time: 4:00 pm https://youtu.be/1SyGyeMmWoM Wednesday, Oct. […]
Topics in Deep Learning Theory Eli Grigsby
Speaker: Andrew Neitzke, Yale University Location: Harvard University Science Center Hall D & via Zoom webinar Dates: October 16 & 17, 2024 Time: 4:00 pm https://youtu.be/1SyGyeMmWoM Wednesday, Oct. 16, […]
Quantum Field Theory and Physical Mathematics Seminar *via Zoom only* Speaker: Rajath Radhakrishnan (ICTP, Trieste) Title: Bosonic and fermionic 1-form symmetries and anomaly matching Abstract: In this talk, I will consider […]
Math and Machine Learning Program Discussion
Member Seminar Speaker: Puskar Mondal Title: Positive mass and rigidity theorems in Riemannian geometry Abstract: Positive mass theorem proved by Schoen-Yau, Witten, Taubes-Parker is one of the most important results in […]
Foundation Seminar (Joint Seminar with BHI) Location: BHI Title: Singularity Theorems, Part I Journal Club Discussion