Mathematics and Machine Learning Program Opening Workshop Dates: September 3 - 5, 2024 Location: Room G10, CMSA, 20 Garden Street, Cambridge MA & via Zoom Webinar AI for Mathematicians, with Leon Bottou, François Charton, David McAllester, Adam Wagner, Boris Hanin, and Geordie Williamson. A series of 6 tutorial lectures introducing concepts of AI and of […]
September 5, 2024 4:00 pm CMSA Common Room, 20 Garden Street, Cambridge MA All CMSA and Math affiliates are invited.
https://www.youtube.com/playlist?list=PL0NRmB0fnLJQS9vXNmNhMlza8r159l72s Youtube Playlist On September 6-7, 2024, the CMSA hosted the tenth annual Conference on Big Data. The Big Data Conference features speakers from the Harvard community as well as scholars from across the globe, with talks focusing on computer science, statistics, math and physics, and economics. Location: Harvard University CMSA, 20 Garden Street, […]
Colloquium Speaker: Lauren Williams, Harvard University Title: Combinatorics and geometry of the amplituhedron Abstract: The amplituhedron is a geometric object introduced by Arkani-Hamed and Trnka to compute scattering amplitudes in N=4 super Yang Mills theory. It generalizes interesting objects such as cyclic polytopes and the positive Grassmannian. It has connections to tropical geometry, cluster algebras, […]
Topics in Deep Learning Theory Eli Grigsby
Open Discussion/Tea
Speaker: Ahsan Khan (CMSA) Title: BPS Algebras in Landau-Ginzburg Models Abstract: The study of BPS states in supersymmetric quantum field theory has been a fruitful source of both mathematical and physical insights. In particular their study often leads to rich algebraic structures - from the "Algebra of the Infrared" of Gaiotto-Moore-Witten to the "Cohomological Hall […]
Math and Machine Learning Program Discussion
Mathematical Physics and Algebraic Geometry Speaker: Justin Kulp (Simons Center for Geometry and Physics) Title: Twisted Tools for (Untwisted) Quantum Field Theory Abstract: One of the most important properties of QFTs is that they can be deformed by "turning on interactions." Essentially every observable can be viewed as coupling the theory to some external system. Famously, adding […]
Topics in Deep Learning Theory Eli Grigsby
https://youtu.be/5Lo7bo7P_I0 Math and Machine Learning Lecture Date: Thursday, Sep. 12, 2024 Time: 4:00 - 5:00 pm Location: Science Center & via Zoom Webinar Speaker: Geordie Williamson, University of Sydney Title: Can AI help with hard mathematics? Abstract: The last years have seen remarkable advances in what AI can do. It is perhaps surprising that […]
Math and Machine Learning Program Discussion