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Advances in Neural Information Processing Systems 28

Peter Flach, Meelis Kull · 2015 · 14.6K citations

Intelligent Information Processing, Computational Neuroscience, Computer Science +2

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

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Engineering, Pde-constrained Optimization, Deep Learning Framework +6

Dropout as a Bayesian Approximation: Representing Model Uncertainty in\n Deep Learning

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Data-driven discovery of partial differential equations

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Weight Uncertainty in Neural Networks

Charles Blundell, Julien Cornebise, Koray Kavukcuoglu et al. · arXiv (Cornell University) · 2015 · 1.3K citations · Full text

Artificial Intelligence, Engineering, Machine Learning +14