The aim of this special issue is to provide a picture of the state-of-the-art and open challenges in machine learning from a statistical physics perspective, mainly that of disordered systems.
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Machine learning and statistical physics: preface
OpenAlex · Neural Networks and Applications · 2020
Abstract
1 Dipartimento di Matematica, Sapienza Università di Roma, Italy 2 Dipartimento di Matematica e Fisica, Università del Salento, Italy 3 Istituto Nazionale di Fisica Nucleare and Istituto Nazionale d’Alta Matematica, Italy 4 Institute for Theoretical Physics, University of Göttingen, Germany 5 Department of Mathematics, King’s College London, United Kingdom 6 Institut de Physique Théorique, CNRS, CEA/SACLAY, Université Paris-Saclay, France 7 EPFL, SPOC laboratory, Switzerland