activity
20172022
most citedTensor Methods in Computer Vision and Deep Learning

182 citations · 195 across the 8 of their papers we have counts for

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Showing cs.LGShow all

5 papers · 1 filter

cs.LG2022

The Spectral Bias of Polynomial Neural Networks

Moulik Choraria, Leello Tadesse Dadi, Grigorios Chrysos +2

Polynomial neural networks (PNNs) have been recently shown to be particularly effective at image generation and face recognition, where high-frequency information is critical. Prev…

cs.LG20223 cited

Controlling the Complexity and Lipschitz Constant improves polynomial nets

Zhenyu Zhu, Fabian Latorre, Grigorios G Chrysos +1

While the class of Polynomial Nets demonstrates comparable performance to neural networks (NN), it currently has neither theoretical generalization characterization nor robustness…

cs.LG2021

CoPE: Conditional image generation using Polynomial Expansions

Grigorios G Chrysos, Markos Georgopoulos, Yannis Panagakis

Generative modeling has evolved to a notable field of machine learning. Deep polynomial neural networks (PNNs) have demonstrated impressive results in unsupervised image generation…

cs.LG2020

nets: Deep Polynomial Neural Networks

Grigorios G. Chrysos, Stylianos Moschoglou, Giorgos Bouritsas +3

Deep Convolutional Neural Networks (DCNNs) is currently the method of choice both for generative, as well as for discriminative learning in computer vision and machine learning. Th…

cs.LG2018

Robust Conditional Generative Adversarial Networks

Grigorios G. Chrysos, Jean Kossaifi, Stefanos Zafeiriou

Conditional generative adversarial networks (cGAN) have led to large improvements in the task of conditional image generation, which lies at the heart of computer vision. The major…