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nucl-th2020
Quantifying Uncertainties on Fission Fragment Mass Yields With Mixture Density Networks
A. E. Lovell, A. T. Mohan, P. Talou
Probabilistic machine learning techniques can learn both complex relations between input features and output quantities of interest as well as take into account stochasticity or un…
physics.comp-ph2020★ 48 cited
Embedding Hard Physical Constraints in Neural Network Coarse-Graining of 3D Turbulence
Arvind T. Mohan, Nicholas Lubbers, Daniel Livescu +1
In the recent years, deep learning approaches have shown much promise in modeling complex systems in the physical sciences. A major challenge in deep learning of PDEs is enforcing…