• Scattering Amplitude from a Twistor Point of View

    CMSA Room G10 CMSA, 20 Garden Street, Cambridge, MA, United States

    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 […]

  • Dolbeault Virasoro algebra and M5 branes

    CMSA Room G10 CMSA, 20 Garden Street, Cambridge, MA, United States

    Quantum Field Theory and Physical Mathematics Seminar Speaker: Brian Williams, Boston University Title: Dolbeault Virasoro algebra and M5 branes Abstract: The worldvolume theory on a stack of M5 branes in M-theory is superconformal. We propose a conjecture that in the holomorphic twist of the theory on a stack of M5 branes an infinite-dimensional enhancement of […]

  • Topics in Deep Learning Theory

    CMSA Room G10 CMSA, 20 Garden Street, Cambridge, MA, United States

    Topics in Deep Learning Theory Eli Grigsby

  • Topics in Deep Learning Theory

    CMSA Room G10 CMSA, 20 Garden Street, Cambridge, MA, United States

    Topics in Deep Learning Theory Eli Grigsby

  • Continuation of solutions of Einstein’s equations

    CMSA Room G10 CMSA, 20 Garden Street, Cambridge, MA, United States

    General Relativity Seminar Speaker: Oswaldo Vazquez, Northeastern University Title: Continuation of solutions of Einstein's equations Abstract: Klainerman-Rodnianski improved the continuation criterion for the solutions of Einstein's equations proved by Michael Anderson using Kirchoff-Sobolev type parametrix and geometric Littlewood-Paley theory. Using their technique but a new parametrix we prove a continuation condition in the context of […]

  • Local complexity measures in modern parameterized function classes for supervised learning

    CMSA Room G10 CMSA, 20 Garden Street, Cambridge, MA, United States

    Colloquium Speaker: Elisenda Grigsby, Boston College Title: Local complexity measures in modern parameterized function classes for supervised learning Abstract: The parameter space for any fixed architecture of neural networks serves as a proxy during training for the associated class of functions - but how faithful is this representation? For any fixed feedforward ReLU network architecture, it […]

  • High-dimensional learning of narrow neural networks

    CMSA Room G10 CMSA, 20 Garden Street, Cambridge, MA, United States

    Member Seminar Speaker: Hugo Cui, CMSA Title: High-dimensional learning of narrow neural networks Abstract: This talk explores the interplay between neural network architectures and data structure through the lens of high-dimensional asymptotics. We focus on a class of narrow neural networks, namely networks possessing a finite number of hidden units, while operating in high dimensions. In the […]