3 papers
physics.plasm-ph2026
Bayesian Active Learning of Ion Loss-Cone Boundaries in Tokamaks
Omar E. Lopez, Minglei Yang, Mark Cianciosa +1
Loss-cone boundary determination in tokamaks is cast as an active learning problem in which a Bayesian logistic regression model with radial basis function features acts as the lea…
physics.comp-ph2025
Exploring the Capabilities of the Frontier Large Language Models for Nuclear Energy Research
Ahmed Almeldein, Mohammed Alnaggar, Rick Archibald +47
The AI for Nuclear Energy workshop at Oak Ridge National Laboratory evaluated the potential of Large Language Models (LLMs) to accelerate fusion and fission research. Fourteen inte…
cs.LG2019
Cluster, Classify, Regress: A General Method For Learning Discountinous Functions
David E. Bernholdt, Mark R. Cianciosa, Clement Etienam +3
This paper presents a method for solving the supervised learning problem in which the output is highly nonlinear and discontinuous. It is proposed to solve this problem in three st…