Статьи, принятые к публикации

Data-Driven Identification of Quadratic Representations for Nonlinear Hamiltonian Systems using Weakly Symplectic Liftings Süleyman Yıldız, Pawan Goyal, Thomas Bendokat, Peter Benner

Süleyman Yıldız
Max Planck Institute for Dynamics of Complex Technical Systems,

Pawan Goyal
Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany

Thomas Bendokat
Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany

Peter Benner
Computational Methods in Systems and Control Theory, Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstr. 1, 39106 Magdeburg, Germany

DOI: 10.1615/JMachLearnModelComput.2024052810

Role of physics in physics-informed machine learning Abhishek Chandra, Joseph Bakarji, Daniel Tartakovsky

Abhishek Chandra
Eindhoven University of Technology

Joseph Bakarji
American University of Beirut

Daniel Tartakovsky
Stanford University

DOI: 10.1615/JMachLearnModelComput.2024053170

Predicting fluid particle trajectories without flow computations: A data-driven approach Jianchen Wei, Melissa Green, Lixin Shen, Minghao Rostami

Jianchen Wei
Syracuse University

Melissa Green
University of Minnesota, Minneapolis

Lixin Shen
Syracuse University

Minghao Rostami
Binghamton University

DOI: 10.1615/JMachLearnModelComput.2024052000

GPT vs Human for Scientific Reviews: A Dual Source Review on Applications of ChatGPT in Science Chenxi Wu, Alan John Varghese, Vivek Oommen, George Em Karniadakis

Chenxi Wu
School of Engineering, Brown University, Providence, Rhode Island, 02912, USA

Alan John Varghese
School of Engineering, Brown University, Providence, Rhode Island, 02912,USA

Vivek Oommen
School of Engineering, Brown University, Providence, Rhode Island, 02912,USA

George Em Karniadakis
School of Engineering, Brown University, Providence, Rhode Island, 02912,USA; Division of Applied Mathematics, Brown University, Providence, Rhode Island,02912, USA

DOI: 10.1615/JMachLearnModelComput.2024052432

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