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Learning Everywhere: A Taxonomy for the Integration of Machine Learning
  and Simulations

Learning Everywhere: A Taxonomy for the Integration of Machine Learning and Simulations

29 September 2019
Geoffrey C. Fox
S. Jha
    AI4CE
ArXivPDFHTML

Papers citing "Learning Everywhere: A Taxonomy for the Integration of Machine Learning and Simulations"

5 / 5 papers shown
Title
Surrogate modeling of Cellular-Potts Agent-Based Models as a segmentation task using the U-Net neural network architecture
Surrogate modeling of Cellular-Potts Agent-Based Models as a segmentation task using the U-Net neural network architecture
Tien Comlekoglu
J. Q. Toledo-Marín
Tina Comlekoglu
Douglas W. DeSimone
Shayn M. Peirce
Geoffrey C. Fox
J. Glazier
64
1
0
01 May 2025
AI-coupled HPC Workflows
AI-coupled HPC Workflows
S. Jha
V. Pascuzzi
Matteo Turilli
24
9
0
24 Aug 2022
Scalable HPC and AI Infrastructure for COVID-19 Therapeutics
Scalable HPC and AI Infrastructure for COVID-19 Therapeutics
Hyungro Lee
André Merzky
Li Tan
Mikhail Titov
Matteo Turilli
...
Anda Trifan
Hubertus Van Dam
S. Wan
Sean R. Wilkinson
S. Jha
46
10
0
20 Oct 2020
An Energy Approach to the Solution of Partial Differential Equations in
  Computational Mechanics via Machine Learning: Concepts, Implementation and
  Applications
An Energy Approach to the Solution of Partial Differential Equations in Computational Mechanics via Machine Learning: Concepts, Implementation and Applications
E. Samaniego
C. Anitescu
S. Goswami
Vien Minh Nguyen-Thanh
Hongwei Guo
Khader M. Hamdia
Timon Rabczuk
X. Zhuang
PINN
AI4CE
159
1,342
0
27 Aug 2019
Time-lagged autoencoders: Deep learning of slow collective variables for
  molecular kinetics
Time-lagged autoencoders: Deep learning of slow collective variables for molecular kinetics
C. Wehmeyer
Frank Noé
AI4CE
BDL
109
355
0
30 Oct 2017
1