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10 papers · 1 filter
Invariant Causal Imitation Learning for Generalizable Policies
Ioana Bica, Daniel Jarrett, Mihaela van der Schaar
Consider learning an imitation policy on the basis of demonstrated behavior from multiple environments, with an eye towards deployment in an unseen environment. Since the observabl…
Time-series Generation by Contrastive Imitation
Daniel Jarrett, Ioana Bica, Mihaela van der Schaar
Consider learning a generative model for time-series data. The sequential setting poses a unique challenge: Not only should the generator capture the conditional dynamics of (stepw…
Physics-informed Bayesian inference of external potentials in classical density-functional theory
Antonio Malpica-Morales, Peter Yatsyshin, Miguel A. Duran-Olivencia +1
The swift progression of machine learning (ML) has not gone unnoticed in the realm of statistical mechanics. ML techniques have attracted attention by the classical density-functio…
Probing magnetic fields in the circumgalactic medium using polarization data from MIGHTEE
K. Böckmann, M. Brüggen, V. Heesen +10
The detection and study of magnetic fields surrounding galaxies is important to understand galaxy evolution since magnetic fields are tracers for dynamical processes in the circumg…
Wasserstein PAC-Bayes Learning: Exploiting Optimisation Guarantees to Explain Generalisation
Maxime Haddouche, Benjamin Guedj
PAC-Bayes learning is an established framework to both assess the generalisation ability of learning algorithms, and design new learning algorithm by exploiting generalisation boun…
The realisation of fast X-ray computed tomography using a limited number of projection images for dimensional metrology
Wenjuan Sun, Stephan Chretien, Ander Biguri +3
Due to the merit of establishing volumetric data, X-ray computed tomography (XCT) is increasingly used as a non-destructive evaluation technique in the quality control of advanced…