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Found 4 papers, 1 papers with code
The Physics of Machine Learning: An Intuitive Introduction for the Physical Scientist
This article is intended for physical scientists who wish to gain deeper insights into machine learning algorithms which we present via the domain they know best, physics.
The Autodidactic Universe
We discover maps that put each of these matrix models in correspondence with both a gauge/gravity theory and a mathematical model of a learning machine, such as a deep recurrent, cyclic neural network.
Deep Learning the Morphology of Dark Matter Substructure
With thousands of strong lensing images anticipated with the coming launch of LSST, we expect that supervised and unsupervised deep learning models will play a crucial role in determining the nature of dark matter.
Cosmology and Nongalactic Astrophysics Instrumentation and Methods for Astrophysics High Energy Physics - Phenomenology
Novel Substructure and Superfluid Dark Matter
The recent observation of the distribution of accreted stars (SDSS-Gaia DR2) suggests that a non-trivial fraction of dark matter is contained within halo substructure.
Cosmology and Nongalactic Astrophysics Astrophysics of Galaxies General Relativity and Quantum Cosmology High Energy Physics - Phenomenology High Energy Physics - Theory
