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20162023
most citedOn the Heavy-Tailed Theory of Stochastic Gradient Descent for Deep Neural Networks

21 citations · 61 across the 9 of their papers we have counts for

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Showing cs.SDShow all

5 papers · 1 filter

cs.SD2022

Exploiting Device and Audio Data to Tag Music with User-Aware Listening Contexts

Karim M. Ibrahim, Elena V. Epure, Geoffroy Peeters +1

As music has become more available especially on music streaming platforms, people have started to have distinct preferences to fit to their varying listening situations, also know…

cs.SD20212 cited

DarkGAN: Exploiting Knowledge Distillation for Comprehensible Audio Synthesis with GANs

Javier Nistal, Stefan Lattner, Gaël Richard

Generative Adversarial Networks (GANs) have achieved excellent audio synthesis quality in the last years. However, making them operable with semantically meaningful controls remain…

cs.SD2021

VQCPC-GAN: Variable-Length Adversarial Audio Synthesis Using Vector-Quantized Contrastive Predictive Coding

Javier Nistal, Cyran Aouameur, Stefan Lattner +1

Influenced by the field of Computer Vision, Generative Adversarial Networks (GANs) are often adopted for the audio domain using fixed-size two-dimensional spectrogram representatio…

cs.SD2021

Self-Supervised VQ-VAE for One-Shot Music Style Transfer

Ondřej Cífka, Alexey Ozerov, Umut Şimşekli +1

Neural style transfer, allowing to apply the artistic style of one image to another, has become one of the most widely showcased computer vision applications shortly after its intr…

cs.SD2016

Robust Downbeat Tracking Using an Ensemble of Convolutional Networks

S. Durand, J. P. Bello, B. David +1

In this paper, we present a novel state of the art system for automatic downbeat tracking from music signals. The audio signal is first segmented in frames which are synchronized a…