8 citations · 18 across the 16 of their papers we have counts for
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cs.LG2023
Adversarial Training Using Feedback Loops
Ali Haisam Muhammad Rafid, Adrian Sandu
Deep neural networks (DNN) have found wide applicability in numerous fields due to their ability to accurately learn very complex input-output relations. Despite their accuracy and…
cs.LG2023★ 1 cited
Neural Network Reduction with Guided Regularizers
Ali Haisam Muhammad Rafid, Adrian Sandu
Regularization techniques such as and regularizers are effective in sparsifying neural networks (NNs). However, to remove a certain neuron or channe…
cs.LG2021
Investigation of Nonlinear Model Order Reduction of the Quasigeostrophic Equations through a Physics-Informed Convolutional Autoencoder
Rachel Cooper, Andrey A. Popov, Adrian Sandu
Reduced order modeling (ROM) is a field of techniques that approximates complex physics-based models of real-world processes by inexpensive surrogates that capture important dynami…