A Customer Relationship Management Case Study Based on Banking Data. - Ivan Luciano Danesi; Cristina Rea (MOD, 2016)

Scenario adaptive disruption prediction study for next generation burning-plasma tokamaks. - Jinxiang Zhu; Cristina Rea; Robert S. Granetz; Earl S. Marmar; Kevin J. Montes; Ryan Sweeney; Roy A. Tinguely; Dalong Chen; Biao Shen; Bingjia Xiao; David Humphreys; Jayson Barr; et al. (CoRR, 2021)

Hybridizing Physics and Neural ODEs for Predicting Plasma Inductance Dynamics in Tokamak Fusion Reactors. - Allen M. Wang; Darren T. Garnier; Cristina Rea (CoRR, 2023)

Position: Opportunities Exist for Machine Learning in Magnetic Fusion Energy. - Lucas Spangher; Allen M. Wang; Andrew Maris; Myles Stapelberg; Viraj Mehta; Alex Saperstein; Stephen Lane-Walsh; Akshata Kishore Moharir; Alessandro Pau; Cristina Rea (ICML, 2024)

Active Disruption Avoidance and Trajectory Design for Tokamak Ramp-downs with Neural Differential Equations and Reinforcement Learning. - Allen M. Wang; Oswin So; Charles Dawson 001; Darren T. Garnier; Cristina Rea; Chuchu Fan (CoRR, 2024)

Time Series Viewmakers for Robust Disruption Prediction. - Dhruva Chayapathy; Tavis Siebert; Lucas Spangher; Akshata Kishore Moharir; Om Manoj Patil; Cristina Rea (CoRR, 2024)

Learning Plasma Dynamics and Robust Rampdown Trajectories with Predict-First Experiments at TCV. - Allen M. Wang; Alessandro Pau; Cristina Rea; Oswin So; Charles Dawson 001; Olivier Sauter; Mark D. Boyer; Anna Vu; Cristian Galperti; Chuchu Fan; Antoine Merle; Yoeri Poels; et al. (CoRR, 2025)