14:00-14.30 Speaker: Koji Hashimoto (Kyoto university) Title: "Neural network representation of quantum systems" Abstract: We provide a novel map with which a wide class of quantum mechanical systems can be cast into the form of a neural network with a statistical summation over network parameters. Our simple idea is to use the universal approximation theorem of neural networks to generate arbitrary paths in the Feynman's path integral. The map can be applied to interacting quantum systems / field theories, even away from the Gaussian limit. Our findings bring machine learning closer to the quantum world. The talk is based on a collaboration with Y. Hirono, J. Maeda and J. Totsuka-Yoshinaka, https://arxiv.org/abs/2403.11420 14:30-15:00 Speaker: Akio Tomiya (Tokyo Woman's Christian University) Title: "CASK: A Gauge Covariant Transformer for Lattice Gauge Theory" Abstract: We introduce a Transformer architecture for lattice QCD that is designed to respect the gauge symmetry and the discrete rotational and translational symmetries of the lattice. The core innovation lies in defining the attention matrix via a Frobenius inner product between link variables and extended staples, ensuring gauge covariance. We apply this method to self-learning HMC and find that it surpasses existing gauge covariant neural networks in performance, demonstrating its potential to enhance lattice QCD computations. This talk is based on arXiv:2501.16955.