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07/10/2023
Code Generation for Machine Learning using Model-Driven Engineering and SysML
Data-driven engineering refers to systematic data collection and process...
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03/25/2023
Heat flux for semi-local machine-learning potentials
The Green-Kubo (GK) method is a rigorous framework for heat transport si...
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09/24/2021
Coupling Microscopic Mobility and Mobile Network Emulation for Pedestrian Communication Applications
Network emulation is a well-established method for demonstrating and tes...
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03/26/2020
Representations of molecules and materials for interpolation of quantum-mechanical simulations via machine learning
Computational study of molecules and materials from first principles is ...
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11/06/2019
Assessing the Frontier: Active Learning, Model Accuracy, and Multi-objective Materials Discovery and Optimization
Discovering novel materials can be greatly accelerated by iterative mach...
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01/16/2015
Understanding Kernel Ridge Regression: Common behaviors from simple functions to density functionals
Accurate approximations to density functionals have recently been obtain...
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04/04/2014
Understanding Machine-learned Density Functionals
Kernel ridge regression is used to approximate the kinetic energy of non...
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06/07/2013
Orbital-free Bond Breaking via Machine Learning
Machine learning is used to approximate the kinetic energy of one dimens...
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12/22/2011
Finding Density Functionals with Machine Learning
Machine learning is used to approximate density functionals. For the mod...
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09/12/2011
