Turbulence theories and statistical closure approaches

Y Zhou - Physics Reports, 2021 - Elsevier
When discussing research in physics and in science more generally, it is common to ascribe
equal importance to the three components of the scientific trinity: theoretical, experimental …

2022 review of data-driven plasma science

R Anirudh, R Archibald, MS Asif… - … on Plasma Science, 2023 - ieeexplore.ieee.org
Data-driven science and technology offer transformative tools and methods to science. This
review article highlights the latest development and progress in the interdisciplinary field of …

Deep neural network initialization with decision trees

KD Humbird, JL Peterson… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
In this paper, a novel, automated process for constructing and initializing deep feedforward
neural networks based on decision trees is presented. The proposed algorithm maps a …

Building high accuracy emulators for scientific simulations with deep neural architecture search

MF Kasim, D Watson-Parris, L Deaconu… - Machine Learning …, 2021 - iopscience.iop.org
Computer simulations are invaluable tools for scientific discovery. However, accurate
simulations are often slow to execute, which limits their applicability to extensive parameter …

[图书][B] Uncertainty quantification and predictive computational science

RG McClarren, P McClarren, R Penrose - 2018 - Springer
This book began as a collection of notes from a class on “predictive science” that I started
teaching in 2009 at Texas A&M University. Initially, the course was in the statistics …

[HTML][HTML] Making inertial confinement fusion models more predictive

JA Gaffney, ST Brandon, KD Humbird, MKG Kruse… - Physics of …, 2019 - pubs.aip.org
Computer models of inertial confinement fusion (ICF) implosions play an essential role in
experimental design and interpretation as well as our understanding of fundamental physics …

A massively parallel infrastructure for adaptive multiscale simulations: modeling RAS initiation pathway for cancer

F Di Natale, H Bhatia, TS Carpenter, C Neale… - Proceedings of the …, 2019 - dl.acm.org
Computational models can define the functional dynamics of complex systems in
exceptional detail. However, many modeling studies face seemingly incommensurate …

Transfer learning to model inertial confinement fusion experiments

KD Humbird, JL Peterson, BK Spears… - … on Plasma Science, 2019 - ieeexplore.ieee.org
Inertial confinement fusion (ICF) experiments are designed using computer simulations that
are approximations of reality and therefore must be calibrated to accurately predict …

Progress of indirect drive inertial confinement fusion in the United States

JL Kline, SH Batha, LR Benedetti, D Bennett… - Nuclear …, 2019 - iopscience.iop.org
Indirect drive converts high power laser light into x-rays using small high-Z cavities called
hohlraums. X-rays generated at the hohlraum walls drive a capsule filled with deuterium …

Deep learning: A guide for practitioners in the physical sciences

BK Spears, J Brase, PT Bremer, B Chen, J Field… - Physics of …, 2018 - pubs.aip.org
Machine learning is finding increasingly broad applications in the physical sciences. This
most often involves building a model relationship between a dependent, measurable output …