75 citations · 156 across the 22 of their papers we have counts for
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cs.LG2019★ 3 cited
Training Generative Adversarial Networks from Incomplete Observations using Factorised Discriminators
Daniel Stoller, Sebastian Ewert, Simon Dixon
Generative adversarial networks (GANs) have shown great success in applications such as image generation and inpainting. However, they typically require large datasets, which are o…
cs.SD2019
Investigating kernel shapes and skip connections for deep learning-based harmonic-percussive separation
Carlos Lordelo, Emmanouil Benetos, Simon Dixon +1
In this paper we propose an efficient deep learning encoder-decoder network for performing Harmonic-Percussive Source Separation (HPSS). It is shown that we are able to greatly red…