Hybrid analysis and modeling, eclecticism, and multifidelity computing toward digital twin revolution

26 March 2021

Papers citing "Hybrid analysis and modeling, eclecticism, and multifidelity computing toward digital twin revolution"

7 / 7 papers shown

Title
Sparse deep neural networks for modeling aluminum electrolysis dynamics E. Lundby Adil Rasheed I. Halvorsen J. Gravdahl 8 14 0 13 Sep 2022
Decentralized digital twins of complex dynamical systems Omer San Suraj Pawar Adil Rasheed AI4CE 28 11 0 07 Jul 2022
Combining physics-based and data-driven techniques for reliable hybrid analysis and modeling using the corrective source term approach Sindre Stenen Blakseth Adil Rasheed T. Kvamsdal Omer San AI4CE 12 31 0 07 Jun 2022
Physics guided machine learning using simplified theories Suraj Pawar Omer San Burak Aksoylu Adil Rasheed T. Kvamsdal PINN AI4CE 92 87 0 18 Dec 2020
A Probabilistic Graphical Model Foundation for Enabling Predictive Digital Twins at Scale Michael G. Kapteyn Jacob V. R. Pretorius Karen E. Willcox 32 213 0 10 Dec 2020
Combining Machine Learning with Knowledge-Based Modeling for Scalable Forecasting and Subgrid-Scale Closure of Large, Complex, Spatiotemporal Systems Alexander Wikner Jaideep Pathak Brian Hunt M. Girvan T. Arcomano I. Szunyogh Andrew Pomerance Edward Ott AI4CE 62 70 0 10 Feb 2020
A Survey on Deep Learning in Medical Image Analysis G. Litjens Thijs Kooi B. Bejnordi A. Setio F. Ciompi Mohsen Ghafoorian Jeroen van der Laak Bram van Ginneken C. I. Sánchez OOD 278 10,599 0 19 Feb 2017