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Development and evaluation of granular simulation for integrating computational thinking into computational physics courses. [PDF]
Educ Inf Technol (Dordr), 2022 Computational thinking (CT) is an essential skill in the twenty-first century. The computational physics course (CPC) is one subject that is designed to support students in the practice of CT.
Muliyati D +6 more
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Deep Learning and Computational Physics (Lecture Notes) [PDF]
arXiv.org, 2023 These notes were compiled as lecture notes for a course developed and taught at the University of the Southern California. They should be accessible to a typical engineering graduate student with a strong background in Applied Mathematics.
Deep Ray, Orazio Pinti, Assad A. Oberai
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Active learning algorithm for computational physics [PDF]
Physical Review Research, 2020 In large-scale computations of physical problems, one often encounters the situation of having to determine a multidimensional function, which can be numerically costly when computing each point in this multidimensional space is already time-demanding ...
Juan Yao +4 more
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Inverse Modeling for Artifact Removal in Photonic Data: A Computational Physics and Transfer Learning-Based Approach. [PDF]
J Chem Inf ModelVulchi RT +4 more
europepmc +2 more sources
Physicality, modeling, and agency in a computational physics class [PDF]
Physical Review Physics Education Research, 2022 Computation is intertwined with essentially all aspects of physics research and is invaluable for physicists' careers. Despite its disciplinary importance, integration of computation into physics education remains a challenge and, moreover, has tended to
A. M. Phillips +4 more
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Data augmentation and feature selection for automatic model recommendation in computational physics [PDF]
Mathematical and Computational Applications, 2021 Classification algorithms have recently found applications in computational physics for the selection of numerical methods or models adapted to the environment and the state of the physical system.
Thomas Daniel +3 more
semanticscholar +1 more source
iScience, 2023 Summary: With pre-trained large models and their associated fine-tuning paradigms being constantly applied in deep learning, the performance of large models achieves a dramatic boost, mostly owing to the improvements on both data quantity and quality ...
Xinyu Pan +9 more
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Applied Sciences, 2022 Prevention of type-1 human immunodeficiency virus (HIV) infections has primarily been through condom usage, abstinence, and behavioral and risk awareness programs.
Jeramy Lewis, Robert E. Camley
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Physics for neuromorphic computing [PDF]
Nature Reviews Physics, 2020 Neuromorphic computing takes inspiration from the brain to create energy efficient hardware for information processing, capable of highly sophisticated tasks. In this article, we make the case that building this new hardware necessitates reinventing electronics. We show that research in physics and material science will be key to create artificial nano-
Danijela Marković +3 more
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Parameterized neural ordinary differential equations: applications to computational physics problems [PDF]
Proceedings of the Royal Society A, 2020 This work proposes an extension of neural ordinary differential equations (NODEs) by introducing an additional set of ODE input parameters to NODEs. This extension allows NODEs to learn multiple dynamics specified by the input parameter instances.
Kookjin Lee, E. Parish
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