Search Results for author:
Found 2 papers, 1 papers with code
Instead of Rewriting Foreign Code for Machine Learning, Automatically Synthesize Fast Gradients
Applying differentiable programming techniques and machine learning algorithms to foreign programs requires developers to either rewrite their code in a machine learning framework, or otherwise provide derivatives of the foreign code.
Highly-scalable, physics-informed GANs for learning solutions of stochastic PDEs
Uncertainty quantification for forward and inverse problems is a central challenge across physical and biomedical disciplines.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
