Editing Machine learning (section)

===Statistical physics===
Analytical and computational techniques derived from deep-rooted physics of disordered systems can be extended to large-scale problems, including machine learning, e.g., to analyse the weight space of [[deep neural network]]s.<ref name=SP_1>{{cite journal| author1=Ramezanpour, A.| author2=Beam, A.L.| author3=Chen, J.H.| author4=Mashaghi, A.| title=Statistical Physics for Medical Diagnostics: Learning, Inference, and Optimization Algorithms| journal=Diagnostics| date=17 November 2020| volume=10| issue=11| page=972| doi=10.3390/diagnostics10110972| doi-access=free| pmid=33228143| pmc=7699346}}</ref> Statistical physics is thus finding applications in the area of [[medical diagnostics]].<ref name=SP_2>{{cite journal| title=Statistical physics of medical diagnostics: Study of a probabilistic model| author1=Mashaghi, A.| author2=Ramezanpour, A. | journal=[[Physical Review E]]| volume=97| date=16 March 2018| issue=3–1| page=032118| doi=10.1103/PhysRevE.97.032118| pmid=29776109| arxiv=1803.10019| bibcode=2018PhRvE..97c2118M| s2cid=4955393}}</ref>