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Mark B. Sandler

Queen Mary University of London

16 papers hereh-index 4810.3k citations487 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • last author16

Across the 16 of 16 papers where every author was matched, so the position is known.

fields
  • cs.SD8
  • cs.AI3
  • cs.DS1
  • cs.IR1
  • cs.LG1
  • cs.MM1
affiliations
  • Queen Mary University of London

identity via Semantic Scholar / OpenAlex

activity
20162022
most citedExplaining Deep Convolutional Neural Networks on Music Classification

32 citations · 45 across the 10 of their papers we have counts for

collaborators
Showing cs.AIShow all

3 papers · 1 filter

cs.AI2020

A Critical Look at the Applicability of Markov Logic Networks for Music Signal Analysis

Johan Pauwels, György Fazekas, Mark B. Sandler

In recent years, Markov logic networks (MLNs) have been proposed as a potentially useful paradigm for music signal analysis. Because all hidden Markov models can be reformulated as…

cs.AI2016

Towards Playlist Generation Algorithms Using RNNs Trained on Within-Track Transitions

Keunwoo Choi, George Fazekas, Mark Sandler

We introduce a novel playlist generation algorithm that focuses on the quality of transitions using a recurrent neural network (RNN). The proposed model assumes that optimal transi…

cs.AI2016

Text-based LSTM networks for Automatic Music Composition

Keunwoo Choi, George Fazekas, Mark Sandler

In this paper, we introduce new methods and discuss results of text-based LSTM (Long Short-Term Memory) networks for automatic music composition. The proposed network is designed t…

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