Journal of Machine Learning for Modeling and Computing
Latest Publications

TOTAL DOCUMENTS

(FIVE YEARS 18)

H-INDEX

(FIVE YEARS 1)

Published By Begell House

2689-3967

Latest Documents Most Cited Documents Contributed Authors Related Sources Related Keywords

Fully Convolutional Spatio-Temporal Models for Representation Learning in Plasma Science

Journal of Machine Learning for Modeling and Computing ◽

10.1615/jmachlearnmodelcomput.2021037052 ◽

2021 ◽

Author(s):

Ge Dong ◽

Kyle Felker ◽

Alexey Svyatkovskiy ◽

William Tang ◽

Julian Kates-Harbeck

Keyword(s):

Representation Learning ◽

Temporal Models ◽

Plasma Science ◽

Spatio Temporal

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CONSTRAINED GAUSSIAN PROCESS REGRESSION: AN ADAPTIVE APPROACH FOR THE ESTIMATION OF HYPERPARAMETERS AND THE VERIFICATION OF CONSTRAINTS WITH HIGH PROBABILITY

Journal of Machine Learning for Modeling and Computing ◽

10.1615/jmachlearnmodelcomput.2021039837 ◽

2021 ◽

Vol 2 (2) ◽

pp. 55-76

Author(s):

Guillaume Perrin ◽

S. Da Veiga

Keyword(s):

Gaussian Process ◽

High Probability ◽

Gaussian Process Regression ◽

Adaptive Approach

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Transfer Learning on Multi-Fidelity Data

Journal of Machine Learning for Modeling and Computing ◽

10.1615/jmachlearnmodelcomput.2021038925 ◽

2021 ◽

Author(s):

Dong Hee Song ◽

Daniel Tartakovsky

Keyword(s):

Transfer Learning

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Dynamic Mode Decomposition for Construction of Reduced-Order Models of Hyperbolic Problems with Shocks

Journal of Machine Learning for Modeling and Computing ◽

10.1615/jmachlearnmodelcomput.2021036132 ◽

2021 ◽

Author(s):

Hannah Lu ◽

Daniel Tartakovsky

Keyword(s):

Dynamic Mode Decomposition ◽

Dynamic Mode ◽

Reduced Order Models ◽

Hyperbolic Problems ◽

Reduced Order ◽

Mode Decomposition

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Imputation of Contiguous Gaps and Extremes of Subhourly Groundwater Time Series Using Random Forests

Journal of Machine Learning for Modeling and Computing ◽

10.1615/jmachlearnmodelcomput.2021038774 ◽

2021 ◽

Author(s):

Dipankar Dwivedi ◽

Utkarsh Mital ◽

Boris Faybishenko ◽

Baptiste Dafflon ◽

Charuleka Varadharajan ◽

...

Keyword(s):

Time Series ◽

Random Forests

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Improving neural network predictions of material properties with limited data using transfer learning

Journal of Machine Learning for Modeling and Computing ◽

10.1615/jmachlearnmodelcomput.2021035199 ◽

2021 ◽

Author(s):

Schuyler Krawczuk ◽

Daniele Venturi

Keyword(s):

Neural Network ◽

Transfer Learning ◽

Material Properties ◽

Limited Data

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DATA-DRIVEN FAILURE PREDICTION IN BRITTLE MATERIALS: A PHASE-FIELD BASED MACHINE LEARNING FRAMEWORK

Journal of Machine Learning for Modeling and Computing ◽

10.1615/jmachlearnmodelcomput.2021034062 ◽

2021 ◽

Author(s):

Eduardo A. Barros de Moraes ◽

Hadi Salehi ◽

Mohsen Zayernouri

Keyword(s):

Machine Learning ◽

Phase Field ◽

Brittle Materials ◽

Failure Prediction ◽

Data Driven ◽

Learning Framework

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A machine learning approach to quantify dissolution kinetics of porous media

Journal of Machine Learning for Modeling and Computing ◽

10.1615/jmachlearnmodelcomput.2021038529 ◽

2021 ◽

Author(s):

Huaxinyu Wang ◽

Chenghai Li ◽

Wei Xing ◽

Yanan Ye ◽

Peng Wang

Keyword(s):

Machine Learning ◽

Porous Media ◽

Dissolution Kinetics ◽

Learning Approach ◽

Machine Learning Approach ◽

Kinetics Of

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Data-informed Emulators for Multi-Physics Simulations

Journal of Machine Learning for Modeling and Computing ◽

10.1615/jmachlearnmodelcomput.2021038577 ◽

2021 ◽

Author(s):

Hannah Lu ◽

Dinara Ermakova ◽

Haruko Murakami Wainwright ◽

Liange Zheng ◽

Daniel Tartakovsky

Keyword(s):

Data Informed

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hp-Variational Physics-Informed Neural Networks for Nonlinear Two-Phase Transport in Porous Media

Journal of Machine Learning for Modeling and Computing ◽

10.1615/jmachlearnmodelcomput.2021038005 ◽

2021 ◽

Author(s):

Mingyuan Yang ◽

John Foster

Keyword(s):

Neural Networks ◽

Porous Media ◽

Two Phase ◽

Transport In Porous Media ◽

Phase Transport

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Journal of Machine Learning for Modeling and ComputingLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Begell House

Fully Convolutional Spatio-Temporal Models for Representation Learning in Plasma Science

CONSTRAINED GAUSSIAN PROCESS REGRESSION: AN ADAPTIVE APPROACH FOR THE ESTIMATION OF HYPERPARAMETERS AND THE VERIFICATION OF CONSTRAINTS WITH HIGH PROBABILITY

Transfer Learning on Multi-Fidelity Data

Dynamic Mode Decomposition for Construction of Reduced-Order Models of Hyperbolic Problems with Shocks

Imputation of Contiguous Gaps and Extremes of Subhourly Groundwater Time Series Using Random Forests

Improving neural network predictions of material properties with limited data using transfer learning

DATA-DRIVEN FAILURE PREDICTION IN BRITTLE MATERIALS: A PHASE-FIELD BASED MACHINE LEARNING FRAMEWORK

A machine learning approach to quantify dissolution kinetics of porous media

Data-informed Emulators for Multi-Physics Simulations

hp-Variational Physics-Informed Neural Networks for Nonlinear Two-Phase Transport in Porous Media

Journal of Machine Learning for Modeling and Computing
Latest Publications