Physics-informed data-driven closure relation for dilute short fiber suspensions by Bruno Ramoa, Chady Ghnatios, João Miguel Nóbrega, Francisco Chinesta

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A Physics-Informed Machine Learning Framework for Permafrost Stability Assessment by Polina Pilyugina, Timofey Chernikov, Maria Smirnova, Alexey Zaytsev, Alexander Bulkin, Evgeny Burnaev, Ilya S. Belalov, Nazar Sotiriadi, Albert Efimov, Yury Maximov, Oleg Anisimov

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Physics-Informed Neural Network-Based Inverse Framework for Time-Fractional Differential Equations for Rheology by Sukirt Thakur, Harsa Mitra, Arezoo M. Ardekani

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An evolutionary game theory-based machine learning framework for predicting mandatory lane change decision by Sixuan Xu, Mengyun Li, Wei Zhou, Jiyang Zhang, Chen Wang

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Streamflow Prediction at the Intersection of Physics and Machine Learning: A Case Study of Two Mediterranean‐Climate Watersheds by S. Adera, D. Bellugi, A. Dhakal, L. Larsen

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A review of physics-informed and data-driven approaches for manufacturing process optimization in polymer matrix composites by Ivan P. Malashin, Dmitry Martysyuk, Vladimir Nelyub, Aleksei Borodulin, Andrei Gantimurov, Vadim Tynchenko

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Learning Constitutive Relations From Soil Moisture Data via Physically Constrained Neural Networks by Toshiyuki Bandai, Teamrat A. Ghezzehei, Peishi Jiang, Patrick Kidger, Xingyuan Chen, Carl I. Steefel

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High‐Resolution National‐Scale Water Modeling Is Enhanced by Multiscale Differentiable Physics‐Informed Machine Learning by Yalan Song, Tadd Bindas, Chaopeng Shen, Haoyu Ji, Wouter J. M. Knoben, Leo Lonzarich, Martyn P. Clark, Jiangtao Liu, Katie vanWerkhoven, Sam Lamont, Matthew Denno, Ming Pan, Yuan Yang, Jeremy Rapp, Mukesh Kumar, Farshid Rahmani, Cyril Thébault, Richard Adkins, James Halgren, Trupesh Patel, Arpita Patel, Kamlesh Arun Sawadekar, Kathryn Lawson

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Pressure swing adsorption process modeling using physics-informed machine learning with transfer learning and labeled data by Zhiqiang Wu, Yunquan Chen, Bingjian Zhang, Jingzheng Ren, Qinglin Chen, Huan Wang, Chang He

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Physics-constrained machine learning for reduced composition space chemical kinetics by Anuj Kumar, Tarek Echekki

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Enhancing Grid Stability Through Physics-Informed Machine Learning Integrated-Model Predictive Control for Electric Vehicle Disturbance Management by Bilal Khan, Zahid Ullah, Giambattista Gruosso

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Advancing deformation calculation: a physics-informed deep graph learning framework for hyperelastic materials by Faras Brumand-Poor, Matthias Trautmann, Katharina Schmitz

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Neuromorphic, physics-informed spiking neural network for molecular dynamics by Vuong Van Pham, Temoor Muther, Amirmasoud Kalantari Dahaghi

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Physics-Informed Neural Networks for the Reynolds Equation with Transient Cavitation Modeling by Faras Brumand-Poor, Florian Barlog, Nils Plückhahn, Matteo Thebelt, Niklas Bauer, Katharina Schmitz

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Univariate Neural Network Quantitative (NNQ) Approximation by Symmetrized Operators by George A. Anastassiou, Seda Karateke, Metin Zontul

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Physics-informed machine learning for building performance simulation-A review of a nascent field by Zixin Jiang, Xuezheng Wang, Han Li, Tianzhen Hong, Fengqi You, Ján Drgoňa, Draguna Vrabie, Bing Dong

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