44 citations · 128 across the 26 of their papers we have counts for
28 papers
Simulation-free and finite-time diffusion model
Kentaro Kaba, Masayuki Ohzeki, Yuki Sughiyama
The performance of generative diffusion models is determined by the choice of the reference diffusion process connecting the empirical and prior distributions. Conventional approac…
Information geometry of chemical reaction networks: Cramer-Rao bound and absolute sensitivity revisited
Dimitri Loutchko, Yuki Sughiyama, Tetsuya J. Kobayashi
Information geometry is based on classical Legendre duality but allows to incorporate additional structure such as algebraic constraints and Bregman divergence functions. It is nat…
Schödinger Bridge Type Diffusion Models as an Extension of Variational Autoencoders
Kentaro Kaba, Reo Shimizu, Masayuki Ohzeki +1
Generative diffusion models use time-forward and backward stochastic differential equations to connect the data and prior distributions. While conventional diffusion models (e.g.,…
Cramer-Rao bound and absolute sensitivity in chemical reaction networks
Dimitri Loutchko, Yuki Sughiyama, Tetsuya J. Kobayashi
Chemical reaction networks (CRN) comprise an important class of models to understand biological functions such as cellular information processing, the robustness and control of met…
Thermodynamic and Stoichiometric Laws Ruling the Fates of Growing Systems
Atsushi Kamimura, Yuki Sughiyama, Tetsuya J. Kobayashi
We delve into growing open chemical reaction systems (CRSs) characterized by autocatalytic reactions within a variable volume, which changes in response to these reactions. Underst…
The Geometry of Thermodynamic Uncertainty Relations in Chemical Reaction Networks
Dimitri Loutchko, Yuki Sughiyama, Tetsuya J. Kobayashi
Recently, Hessian geometry - an extension of information geometry - has emerged as a framework to naturally connect the geometries appearing in the theory of chemical reaction netw…