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Found 3 papers, 1 papers with code
Efficient kernel surrogates for neural network-based regression
For the regression problem of smooth functions and logistic regression classification, we show that the CK performance is only marginally worse than that of the NTK and, in certain cases, is shown to be superior.
A multifidelity approach to continual learning for physical systems
We introduce a novel continual learning method based on multifidelity deep neural networks.
Machine Learning in Heterogeneous Porous Materials
The "Workshop on Machine learning in heterogeneous porous materials" brought together international scientific communities of applied mathematics, porous media, and material sciences with experts in the areas of heterogeneous materials, machine learning (ML) and applied mathematics to identify how ML can advance materials research.
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