A high-bias, low-variance introduction to machine learning for physicists

P Mehta, M Bukov, CH Wang, AGR Day, C Richardson… - Physics reports, 2019 - Elsevier
Abstract Machine Learning (ML) is one of the most exciting and dynamic areas of modern
research and application. The purpose of this review is to provide an introduction to the core …

From stochastic thermodynamics to thermodynamic inference

U Seifert - Annual Review of Condensed Matter Physics, 2019 - annualreviews.org
For a large class of nonequilibrium systems, thermodynamic notions like work, heat, and, in
particular, entropy production can be identified on the level of fluctuating dynamical …

Intensive Urbanization, Urban Meteorology and Air Pollutants: Effects on the Temperature of a City in a Basin Geography

P Pacheco, E Mera, V Fuentes - International Journal of Environmental …, 2023 - mdpi.com
A qualitative study of thermal transfers is carried out from a record of measurements (time
series) of meteorological variables (temperature, relative humidity and magnitude of wind …

Designing a physical quantum agent

MJ Kewming, S Shrapnel, GJ Milburn - Physical Review A, 2021 - APS
The concept of an embodied intelligent agent is a key concept in modern artificial
intelligence and robotics. Physically, an agent is an open system embedded in an …

The physics of learning machines

GJ Milburn, S Basiri-Esfahani - Contemporary Physics, 2022 - Taylor & Francis
ABSTRACT A learning machine, like all machines, is an open system driven far from thermal
equilibrium by access to a low entropy source of free energy. We discuss the connection …

Validity and reliability estimation of assessment ability instrument for data literacy on high school physics material

PE Larasati, DRA Yunanta - Journal of Physics: Conference …, 2020 - iopscience.iop.org
Assessment ability instrument for data literacy of physics material that's not accordance with
characteristics of the assessment, it can make students less understanding of …