The critical temperature of the 2D-Ising model through deep learning autoencoders

On the spectrum and string tension of U(1) lattice gauge theory in 2 + 1 dimensions

(2019) Andreas Athenodorou et al.   JOURNAL OF HIGH ENERGY PHYSICS

Machine Learning as a universal tool for quantitative investigations of phase transitions

(2019) Cinzia Giannetti et al.   NUCLEAR PHYSICS B

Phase transition encoded in neural network

(2019) Kouji Kashiwa et al.   Progress of Theoretical and Experimental Physics

Machine Learning Out-of-Equilibrium Phases of Matter

(2018) Jordan Venderley et al.   PHYSICAL REVIEW LETTERS

Unsupervised machine learning for detection of phase transitions in off-lattice systems. I. Foundations

(2018) R. B. Jadrich et al.   JOURNAL OF CHEMICAL PHYSICS

Learning phase transitions by confusion

(2017) Evert P. L. van Nieuwenburg et al.   Nature Physics

Machine learning phases of matter

(2017) Juan Carrasquilla et al.   Nature Physics

Machine learning quantum phases of matter beyond the fermion sign problem

(2017) Peter Broecker et al.   Scientific Reports

Representational Power of Restricted Boltzmann Machines and Deep Belief Networks

(2008) Nicolas Le Roux et al.   NEURAL COMPUTATION