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Found 3 papers, 2 papers with code
Neural DAEs: Constrained neural networks
This article investigates the effect of explicitly adding auxiliary algebraic trajectory information to neural networks for dynamical systems.
A-Optimal Active Learning
The first is based on a Bayesian interpretation of the semi-supervised learning problem with the graph Laplacian that is used for the prior distribution and the second is based on a frequentist approach, that updates the estimation of the bias term based on the recovery of the labels.
Mimetic Neural Networks: A unified framework for Protein Design and Folding
Recent advancements in machine learning techniques for protein folding motivate better results in its inverse problem -- protein design.
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