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Image-to-image Mapping with Many Domains by Sparse Attribute Transfer
Unsupervised image-to-image translation consists of learning a pair of m...
06/23/2020 ∙ by Matthew Amodio, et al. ∙
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TraVeLGAN: Image-to-image Translation by Transformation Vector Learning
Interest in image-to-image translation has grown substantially in recent...
02/25/2019 ∙ by Matthew Amodio, et al. ∙
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Finding Archetypal Spaces for Data Using Neural Networks
Archetypal analysis is a type of factor analysis where data is fit by a ...
01/25/2019 ∙ by David van Dijk, et al. ∙
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Generating and Aligning from Data Geometries with Generative Adversarial Networks
Unsupervised domain mapping has attracted substantial attention in recen...
01/24/2019 ∙ by Matthew Amodio, et al. ∙
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Graph Spectral Regularization for Neural Network Interpretability
Deep neural networks can learn meaningful representations of data. Howev...
09/30/2018 ∙ by Alexander Tong, et al. ∙
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Neural Attribute Machines for Program Generation
Recurrent neural networks have achieved remarkable success at generating...
05/25/2017 ∙ by Matthew Amodio, et al. ∙
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Matthew Amodio
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University of Wisconsin-Madison
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Yale University
