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Gil Goldshlager

2 accepted papers

2025

Improving Energy Natural Gradient Descent through Woodbury, Momentum, and Randomization

NeurIPS 2025poster

Natural gradient methods significantly accelerate the training of Physics-Informed Neural Networks (PINNs), but are often prohibitively costly. We introduce a suite of techniques to improve the accuracy and efficiency of energy natural gradient descent (ENGD) for PINNs. First, we leverage the Woodbu…

Cited by 0SourceScholar