• Tropicalized quantum field theory

    Virtual

    https://youtu.be/0FCgpyCfb4o New Technologies in Mathematics Seminar Speaker: Michael Borinsky, Perimeter Institute  Title: Tropicalized quantum field theory Abstract: Quantum field theory (QFT) is one of the most accurate methods for making phenomenological predictions in physics, but it has a significant drawback: obtaining concrete predictions from it is computationally very demanding. The standard perturbative approach expands an […]

  • Understanding Optimization in Deep Learning with Central Flows

    Hybrid - G10

    https://youtu.be/04E8r76TetQ New Technologies in Mathematics Seminar Speaker: Alex Damian, Harvard Title: Understanding Optimization in Deep Learning with Central Flows Abstract: Traditional theories of optimization cannot describe the dynamics of optimization in deep learning, even in the simple setting of deterministic training. The challenge is that optimizers typically operate in a complex, oscillatory regime called the "edge of […]

  • The Carleson project: A collaborative formalization

    Virtual

    New Technologies in Mathematics Seminar Speaker: María Inés de Frutos Fernández, Mathematical Institute, University of Bonn Title: The Carleson project: A collaborative formalization Abstract: A well-known result in Fourier analysis establishes that the partial Fourier sums of a smooth periodic function $f$ converge uniformly to $f$, but the situation is a lot more subtle for […]

  • Discovery of unstable singularity with machine precision

    CMSA 20 Garden Street Cambridge, Massachusetts 02138 United States

    New Technologies in Mathematics Seminar Speaker: Yongji Wang, NYU Courant Institute of Mathematical Sciences Title: Discovery of unstable singularity with machine precision Abstract: Whether singularities can form in fluids remains a foundational unanswered question in mathematics. This phenomenon occurs when solutions to governing equations, such as the 3D Euler equations, develop infinite gradients from smooth initial […]

  • Machine learning tools for mathematical discovery

    Virtual

    New Technologies in Mathematics Seminar Speaker: Adam Zsolt Wagner, Google DeepMind Title: Machine learning tools for mathematical discovery Abstract: I will discuss various ML tools we can use today to try to find interesting constructions to various mathematical problems. I will briefly mention simple reinforcement learning setups and PatternBoost, but the talk will mainly focus […]