Colloquium Speaker: Artem Chernikov, University of Maryland Title: Higher Vapnik–Chervonenkis theory Abstract: Finite VC-dimension, a combinatorial property of families of sets, was discovered simultaneously by Vapnik and Chervonenkis in probabilistic learning […]
Topics in Deep Learning Theory Eli Grigsby
Open Discussion/Tea
Geometry and Quantum Theory Seminar Speaker: Thibault Décoppet, Harvard University Title: Fusion 2-Categories and their Classification Abstract: Categorifying the classical notion of fusion (1-)category, fusion 2-categories were recently introduced. These objects […]
Math and Machine Learning Program Discussion
CMSA Q&A Seminar Speaker: Dan Freed, Harvard Mathematics & CMSA Topic: What are topological phases of matter?
https://youtu.be/C6NDdnSaluU New Technologies in Mathematics Seminar Speaker: Aryo Lotfi (EPFL) Title: How Far Can Transformers Reason? The Globality Barrier and Inductive Scratchpad Abstract: Can Transformers predict new syllogisms by composing established ones? […]
Mathematical Physics and Algebraic Geometry Seminar Speaker: Hamza Ahmed, Northeastern University Title: Heterotic Little String Theories and Inequivalent Genus-One Fibrations Abstract: Little String Theories (LSTs) are 6D Supersymmetric quantum field theories (SQFTs) […]
Topics in Deep Learning Theory Eli Grigsby
Quantum Field Theory and Physical Mathematics Seminar Speaker: Luuk Stehouwer, Dalhousie University Title: The spin-statistics theorem for TFTs Abstract: In quantum field theory (QFT) the spin-statistics theorem says that in […]
Math and Machine Learning Program Discussion
Member Seminar Speaker: Ahsan Khan Title: Formality Theorem and Webs Abstract: The “formality theorem” of Kontsevich was a key result that implies that every Poisson manifold admits a deformation quantization. […]