181 citations · 661 across the 28 of their papers we have counts for
5 papers · 1 filter
A domain agnostic measure for monitoring and evaluating GANs
Paulina Grnarova, Kfir Y Levy, Aurelien Lucchi +4
Generative Adversarial Networks (GANs) have shown remarkable results in modeling complex distributions, but their evaluation remains an unsettled issue. Evaluations are essential f…
DeepSphere: Efficient spherical Convolutional Neural Network with HEALPix sampling for cosmological applications
Nathanaël Perraudin, Michaël Defferrard, Tomasz Kacprzak +1
Convolutional Neural Networks (CNNs) are a cornerstone of the Deep Learning toolbox and have led to many breakthroughs in Artificial Intelligence. These networks have mostly been d…
Audio inpainting of music by means of neural networks
Andrés Marafioti, Nicki Holighaus, Piotr Majdak +1
We studied the ability of deep neural networks (DNNs) to restore missing audio content based on its context, a process usually referred to as audio inpainting. We focused on gaps i…
Forecasting Time Series with VARMA Recursions on Graphs
Elvin Isufi, Andreas Loukas, Nathanael Perraudin +1
Graph-based techniques emerged as a choice to deal with the dimensionality issues in modeling multivariate time series. However, there is yet no complete understanding of how the u…
Improving DNN-based Music Source Separation using Phase Features
Joachim Muth, Stefan Uhlich, Nathanael Perraudin +3
Music source separation with deep neural networks typically relies only on amplitude features. In this paper we show that additional phase features can improve the separation perfo…