no code implementations • 29 Feb 2024 • Noboru Isobe, Masanori Koyama, Kohei Hayashi, Kenji Fukumizu
In this paper, we develop the theory of conditional generation based on Flow Matching, a current strong contender of diffusion methods.
no code implementations • 26 Nov 2023 • Noboru Isobe
This study focuses on a Wasserstein-type gradient flow, which represents an optimization process of a continuous model of a Deep Neural Network (DNN).
no code implementations • 9 Mar 2023 • Noboru Isobe, Mizuho Okumura
This paper presents a mathematical analysis of ODE-Net, a continuum model of deep neural networks (DNNs).
