A machine learning approach for efficient uncertainty quantification using multiscale methods

Adam: A Method for Stochastic Optimization

Diederik P. Kingma, Jimmy Ba · UvA-DARE (University of Amsterdam) · 2014 · 84.8K citations · Full text

Computing, Computer Science, Algorithms +16

Dropout: a simple way to prevent neural networks from overfitting

Nitish Srivastava, Geoffrey E. Hinton, Alex Krizhevsky et al. · 2014 · 34.3K citations

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Learning representations by back-propagating errors

David E. Rumelhart, Geoffrey E. Hinton, Ronald J. Williams · Nature · 1986 · 30.9K citations

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Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

Sergey Ioffe, Christian Szegedy · arXiv (Cornell University) · 2015 · 24.4K citations · Full text

Computing, Computer Science, Artificial Intelligence +15

Multilayer feedforward networks are universal approximators

Kurt Hornik, Maxwell B. Stinchcombe, Halbert White · Neural Networks · 1989 · 21.2K citations

Computing, Computer Science, Mathematics +10