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SPECIAL ISSUE:MACHINE LEARNING TECHNIQUES FOR APPLICATIONS IN SUSTAINABILITY RESEARCH  GUEST EDITORS: VALENTINA CIRIELLO& DANIEL M. TARTAKOVSKY  
DOI: 10.1615/JMachLearnModelComput.v3.i2 
Table of Contents: 
MACHINE LEARNING TECHNIQUES FOR APPLICATIONS IN SUSTAINABILITY RESEARCH
Valentina Ciriello, Daniel M. Tartakovsky
Valentina Ciriello 
University of Bologna 
 
 
Daniel M. Tartakovsky 
Department of Energy Science & Engineering, Engineering, Stanford University, 367 Panama St., Stanford, CA 94305, USA 
 
 
 
v-vi pages
 DOI: 10.1615/JMachLearnModelComput.2022045267
  
IMPUTATION OF CONTIGUOUS GAPS AND EXTREMES OF SUBHOURLY GROUNDWATER TIME SERIES USING RANDOM FORESTS
Dipankar  Dwivedi, Utkarsh  Mital, Boris  Faybishenko, Baptiste  Dafflon, Charuleka  Varadharajan, Deborah  Agarwal, Kenneth H. Williams, Carl I.  Steefel, Susan S.  Hubbard
Dipankar  Dwivedi 
Earth and Environmental Sciences Area, Lawrence Berkeley National
Laboratory, Berkeley, CA 94720, USA 
 
 
Utkarsh  Mital 
Earth and Environmental Sciences Area, Lawrence Berkeley National
Laboratory, Berkeley, CA 94720, USA 
 
 
Boris  Faybishenko 
Earth and Environmental Sciences Area, Lawrence Berkeley National
Laboratory, Berkeley, CA 94720, USA 
 
 
Baptiste  Dafflon 
Earth and Environmental Sciences Area, Lawrence Berkeley National
Laboratory, Berkeley, CA 94720, USA 
 
 
Charuleka  Varadharajan 
Earth and Environmental Sciences Area, Lawrence Berkeley National
Laboratory, Berkeley, CA 94720, USA 
 
 
Deborah  Agarwal 
Computational Research Division, Lawrence Berkeley National Laboratory,
Berkeley, CA 94720, USA 
 
 
Kenneth H. Williams 
Earth and Environmental Sciences Area, Lawrence Berkeley National
Laboratory, Berkeley, CA 94720, USA 
 
 
Carl I.  Steefel 
Earth and Environmental Sciences Area, Lawrence Berkeley National
Laboratory, Berkeley, CA 94720, USA 
 
 
Susan S.  Hubbard 
Earth and Environmental Sciences Area, Lawrence Berkeley National
Laboratory, Berkeley, CA 94720, USA 
 
 
 
1-22 pages
 DOI: 10.1615/JMachLearnModelComput.2021038774
  
MULTISTEP AND CONTINUOUS PHYSICS-INFORMED NEURAL NETWORK METHODS FOR LEARNING GOVERNING EQUATIONS AND CONSTITUTIVE RELATIONS
Ramakrishna Tipireddy, Paris Perdikaris, Panos Stinis, Alexandre M. Tartakovsky
Ramakrishna Tipireddy 
Pacific Northwest National Laboratory, MSIN K7-90, Richland,
Washington 99352, USA 
 
 
Paris Perdikaris 
Mechanical Engineering and Applied Mechanics, University of Pennsylvania,
Philadelphia, University of Pennsylvania, Philadelphia, Pennsylvania 19104,
USA 
 
 
Panos Stinis 
Pacific Northwest National Laboratory, MSIN K7-90, Richland,
Washington 99352, USA 
 
 
Alexandre M. Tartakovsky 
Pacific Northwest National Laboratory, MSIN K7-90, Richland, Washington 99352, USA; Department of Civil and Environmental Engineering, University of Illinois Urbana-Champaign, Urbana, Illinois 61801, USA 
 
 
 
23-46 pages
 DOI: 10.1615/JMachLearnModelComput.2022041787
  
INVERSE ANALYSIS WITH VARIATIONAL AUTOENCODERS: A COMPARISON OF SHALLOW AND DEEP NETWORKS
Hao Wu, Daniel  O'Malley, John K.  Golden, Velimir V.  Vesselinov
Hao Wu 
Computational Earth Science, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA 
 
 
Daniel  O'Malley 
Computational Earth Science, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA 
 
 
John K.  Golden 
Information Sciences, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA 
 
 
Velimir V.  Vesselinov 
Computational Earth Science, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA 
 
 
 
47-70 pages
 DOI: 10.1615/JMachLearnModelComput.2022042093
  
GAUSSIAN PROCESS REGRESSION AND CONDITIONAL KARHUNEN-LOÈVE EXPANSION FOR FORWARD UNCERTAINTY QUANTIFICATION AND INVERSE MODELING IN THE PRESENCE OF MEASUREMENT NOISE
Jing Li, Alexandre M. Tartakovsky
Jing Li 
Pacific Northwest National Laboratory, Richland, Washington 99354, USA 
 
 
Alexandre M. Tartakovsky 
Pacific Northwest National Laboratory, MSIN K7-90, Richland, Washington 99352, USA; Department of Civil and Environmental Engineering, University of Illinois Urbana-Champaign, Urbana, Illinois 61801, USA 
 
 
 
71-86 pages
 DOI: 10.1615/JMachLearnModelComput.2022041893
  
ELECTRIC LOAD AND POWER FORECASTING USING ENSEMBLE GAUSSIAN PROCESS REGRESSION
T.  Ma, David A. Barajas-Solano, R.  Huang, Alexandre M. Tartakovsky
T.  Ma 
Pacific Northwest National Laboratory, Richland, Washington 99354, USA 
 
 
David A. Barajas-Solano 
Pacific Northwest National Laboratory, Richland, Washington 99354, USA 
 
 
R.  Huang 
Pacific Northwest National Laboratory, Richland, Washington 99354, USA 
 
 
Alexandre M. Tartakovsky 
Pacific Northwest National Laboratory, MSIN K7-90, Richland, Washington 99352, USA; Department of Civil and Environmental Engineering, University of Illinois Urbana-Champaign, Urbana, Illinois 61801, USA 
 
 
 
87-110 pages
 DOI: 10.1615/JMachLearnModelComput.2022041871
  
 
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