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Volume 6, 2025 / Edição 3

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Table of Contents:

AI-ENABLED CARDIOVASCULAR MODELS TRAINED ON MULTIFIDELITY SIMULATIONS DATA Alessia Chiofalo, L. Careddu, Valentina Ciriello, Daniel M. Tartakovsky

Alessia Chiofalo
University of Bologna

L. Careddu
Pediatric Cardiac Surgery and Adult Congenital Heart Disease Program, Department of Cardio-Thoracic and Vascular Medicine, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy

Valentina Ciriello
University of Bologna

Daniel M. Tartakovsky
Department of Energy Science & Engineering, Engineering, Stanford University, 367 Panama St., Stanford, CA 94305, USA

1-17 páginas
DOI: 10.1615/JMachLearnModelComput.2025058368

DOMAIN DECOMPOSITION FOR ENHANCEMENT OF REDUCED-ORDER MODELS B. Abylkhani, Dipankar Dwivedi, S. B. Yabusaki, Daniel M. Tartakovsky

B. Abylkhani
Department of Energy Science and Engineering, Stanford University, California, USA

Dipankar Dwivedi
Earth and Environmental Sciences Area, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA

S. B. Yabusaki
Pacific Northwest National Laboratory, Richland, Washington, USA

Daniel M. Tartakovsky
Department of Energy Science & Engineering, Engineering, Stanford University, 367 Panama St., Stanford, CA 94305, USA

19-36 páginas
DOI: 10.1615/JMachLearnModelComput.2025059012

CONFORMAL APPROACH TO GAUSSIAN PROCESS SURROGATE EVALUATIONWITH MARGINAL COVERAGE GUARANTEES Edgar Jaber, Vincent Blot, Nicolas J. B. Brunel, Vincent Chabridon, Emmanuel Remy, Bertrand Iooss, Didier Lucor, Mathilde Mougeot, Alessandro Leite

Edgar Jaber
EDF R&D, Centre Borelli, LISN

Vincent Blot
Capgemini Invent, 147 Q. du Pdt. Roosevelt, 92130, Issy-les-Moulineaux, France; Paris-Saclay University, CNRS, Laboratoire Interdisciplinaire des Sciences du Numérique, 91405, Orsay, France

Nicolas J. B. Brunel
Capgemini Invent, 147 Q. du Pdt. Roosevelt, 92130, Issy-les-Moulineaux, France

Vincent Chabridon
EDF R&D, 6 Q. Watier, 78401, Chatou, France

Emmanuel Remy
EDF R&D, 6 Quai Watier, 78401 Chatou, France

Bertrand Iooss
Institut de Mathématiques de Toulouse, 31062 Toulouse, France; EDF Lab Chatou, 78401 Chatou, France

Didier Lucor
LIMSI, CNRS, Université Paris-Saclay, Campus Universitaire bat 508, Rue John von Neumann, F-91405 Orsay cedex, France

Mathilde Mougeot
Université Paris-Saclay, CNRS, ENS Paris-Saclay, Centre Borelli, 91190 Gif-sur-Yvette, France

Alessandro Leite
Paris-Saclay University, CNRS, Laboratoire Interdisciplinaire des Sciences du Numérique, 91405, Orsay, France; ENSIIE, 1 square de la Résistance 91000, Évry-Courcouronnes, France

37-68 páginas
DOI: 10.1615/JMachLearnModelComput.2025054687

CONCURRENT, CONDENSED STEIN VARIATIONAL GRADIENT DESCENT FOR UNCERTAINTY QUANTIFICATION OF NEURAL NETWORKS Govinda Anantha Padmanabha, Cosmin Safta, Nikolaos Bouklas, Reese E. Jones

Govinda Anantha Padmanabha
Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, New York 14853, USA

Cosmin Safta
Sandia National Labs

Nikolaos Bouklas
Cornell University

Reese E. Jones
Sandia National Laboratories, Livermore, California 94551, USA

69-94 páginas
DOI: 10.1615/JMachLearnModelComput.2025059347

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