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: 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. […]
Freedman CMSA Seminar *Note: via Zoom only* 2:00-3:30 pm ET Speaker: Matt Hastings, Microsoft Quantum Program Title: Invertible Phases of Matter and Quantum Cellular Automata: Dimensions One to Three Abstract: […]