Adversarial Domain Adaptation for Identifying Phase Transitions. - Patrick Huembeli; Alexandre Dauphin; Peter Wittek (CoRR, 2017)

Unsupervised machine learning of topological phase transitions from experimental data. - Niklas Käming; Anna Dawid; Korbinian Kottmann; Maciej Lewenstein; Klaus Sengstock; Alexandre Dauphin; Christof Weitenberg (Mach. Learn. Sci. Technol., 2021)

Hessian-based toolbox for reliable and interpretable machine learning in physics. - Anna Dawid; Patrick Huembeli; Michal Tomza; Maciej Lewenstein; Alexandre Dauphin (Mach. Learn. Sci. Technol., 2022)

Citizen Science to Assess Light Pollution with Mobile Phones. - Gorka Muñoz-Gil; Alexandre Dauphin; Federica A. Beduini; Alejandro Sánchez de Miguel (Remote. Sens., 2022)

Learning minimal representations of stochastic processes with variational autoencoders. - Gabriel Fernández-Fernández; Carlo Manzo; Maciej Lewenstein; Alexandre Dauphin; Gorka Muñoz-Gil (CoRR, 2023)

Optimization of Quantum Systems Emulation via a Variant of the Bandwidth Minimization Problem. - Mohamed Yassine Naghmouchi; Joseph Vovrosh; Wesley da Silva Coelho; Alexandre Dauphin (CoDIT, 2024)

A hybrid quantum algorithm to detect conical intersections. - Emiel Koridon; Joana Fraxanet; Alexandre Dauphin; Lucas Visscher; Thomas E. O'Brien; Stefano Polla (Quantum, 2024)

Characterizing out-of-distribution generalization of neural networks: application to the disordered Su-Schrieffer-Heeger model. - Kacper Cybinski; Marcin Plodzien; Michal Tomza; Maciej Lewenstein; Alexandre Dauphin; Anna Dawid (Mach. Learn. Sci. Technol., 2025)