• Marcus Hoskins
  • Publications
  • Talks
  • Teaching
  • Reading
  • Blog Posts
  • CV
  • Guide
    Marcus Hoskins

    Marcus Hoskins

    Physics Ph.D. Student

    • New York University
    • Email
    • Github
    • YouTube

    Neural Network / QFT Correspondence

    This is where we will put reading for the neural network / quantum field theory correspondence.

    Reviews
    • TASI Lectures on Physics for Machine Learning
    • Neural Networks and Quantum Field Theory
    • [Slides] NN-QFT Correspondence
    • [Slides] NN-QFT Correspondence
    Papers
    • Viability of perturbative expansion for quantum field theories on neurons
    • Symmetry-via-Duality: Invariant Neural Network Densities from Parameter-Space Correlators
    • Holography as deep learning
    • Synaptic Field Theory for Neural Networks
    • Quantum Mechanics and Neural Networks
    • Conformal Fields from Neural Networks
    • KAN: Kolmogorov-Arnold Networks
    • Neural network field theories: non-Gaussianity, actions, and locality
    • Building Quantum Field Theories Out of Neurons
    • Infinite neural network quantum states: entanglement and training dynamics
    • Deep Information Propagation
    • [Book] Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
    • [Book] Deep Learning
    Thoughts
    • How can one construct scattering states in the NN-QFT correspondence?
    • Is there a way to impose asymptotic structures in this correspondence?

    Tags: Neural Networks, Quantum Field Theory

    Share on

    Twitter Facebook LinkedIn
    Previous Next
    Sitemap
    • Follow:
    • GitHub
    • Feed
    © 2025 Marcus Hoskins. Powered by Jekyll & AcademicPages, a fork of Minimal Mistakes.