3 papers
physics.plasm-ph2026
Horizon-Aware Early Event Prediction for Tokamak Disruption Alarms
Takeshi Koshizuka, Takaharu Yaguchi
Reliable disruption prediction is essential for the safe operation of future tokamaks. Existing full-distribution survival methods model the complete residual time-to-disruption di…
cs.LG2025
Understanding Generalization in Physics Informed Models through Affine Variety Dimensions
Takeshi Koshizuka, Issei Sato
Physics-informed machine learning is gaining significant traction for enhancing statistical performance and sample efficiency through the integration of physical knowledge. However…
cs.LG2023
Understanding the Expressivity and Trainability of Fourier Neural Operator: A Mean-Field Perspective
Takeshi Koshizuka, Masahiro Fujisawa, Yusuke Tanaka +1
In this paper, we explores the expressivity and trainability of the Fourier Neural Operator (FNO). We establish a mean-field theory for the FNO, analyzing the behavior of the rando…