82 citations · 241 across the 8 of their papers we have counts for
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cs.LG2023★ 5 cited
An operator preconditioning perspective on training in physics-informed machine learning
Tim De Ryck, Florent Bonnet, Siddhartha Mishra +1
In this paper, we investigate the behavior of gradient descent algorithms in physics-informed machine learning methods like PINNs, which minimize residuals connected to partial dif…
cs.LG2023★ 38 cited
Convolutional Neural Operators for robust and accurate learning of PDEs
Bogdan Raonić, Roberto Molinaro, Tim De Ryck +5
Although very successfully used in conventional machine learning, convolution based neural network architectures -- believed to be inconsistent in function space -- have been large…