Math and Machine Learning Program Discussion
CMSA Room G10 CMSA, 20 Garden Street, Cambridge, MA, United StatesMath and Machine Learning Program Discussion
Math and Machine Learning Program Discussion
Member Seminar Speaker: Keyou Zeng Title: Scattering Amplitude from a Twistor Point of View Abstract: Scattering amplitude is a key quantity in quantum field theory. Although challenging to compute at higher loops and for large particle numbers, physicists have developed various tools to gain a deeper understanding of amplitudes. In this seminar, I will introduce […]
Math and Machine Learning Program Discussion
General Relativity Seminar Speaker: Christoph Kehle, MIT Title: Gravitational collapse to extremal Reissner-Nordström and the third law of black hole thermodynamics Abstract: In this talk, I will present a proof that extremal Reissner-Nordström black holes can form in finite time in gravitational collapse of charged matter. In particular, this construction provides a definitive disproof of […]
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 Segal-Stolz-Teichner program, which is one of the most deep and interesting topics relating homotopy theory and physics. Mathematically, they propose a geometric model of TMF, […]
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 (LLMs) evolve from simple word prediction to complex skills, with a focus on mathematical problem solving. A major driver of AI products today is the […]
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, 2024 Title: Abelianization in analysis of ODEs Abstract: I will describe the exact WKB method for asymptotic analysis of families of ODEs in one […]
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, 2024 Title: Abelianization in analysis of ODEs Abstract: I will describe the exact WKB method for asymptotic analysis of families of ODEs in one variable, […]