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2020 – today
- 2023
[c18]Igor Pereira, Felipe Araújo, Filip Korzeniowski, Richard Vogl:
MoisesDB: A Dataset for Source Separation Beyond 4-Stems. ISMIR 2023: 619-626- [i16]Igor Pereira, Felipe Araújo, Filip Korzeniowski, Richard Vogl:
Moisesdb: A dataset for source separation beyond 4-stems. CoRR abs/2307.15913 (2023) - 2022
- [j3]Filip Korzeniowski
, Sergio Oramas, Fabien Gouyon:
Artist Similarity for Everyone: A Graph Neural Network Approach. Trans. Int. Soc. Music. Inf. Retr. 5(1): 129-140 (2022) - [c17]Matthew C. McCallum, Filip Korzeniowski, Sergio Oramas, Fabien Gouyon, Andreas F. Ehmann:
Supervised and Unsupervised Learning of Audio Representations for Music Understanding. ISMIR 2022: 256-263 - [i15]Matthew C. McCallum, Filip Korzeniowski, Sergio Oramas, Fabien Gouyon, Andreas F. Ehmann:
Supervised and Unsupervised Learning of Audio Representations for Music Understanding. CoRR abs/2210.03799 (2022) - 2021
- [c16]Filip Korzeniowski, Sergio Oramas, Fabien Gouyon:
Artist Similarity Using Graph Neural Networks. ISMIR 2021: 350-357 - [i14]Filip Korzeniowski, Sergio Oramas, Fabien Gouyon:
Artist Similarity with Graph Neural Networks. CoRR abs/2107.14541 (2021) - 2020
- [c15]Filip Korzeniowski, Oriol Nieto, Matthew C. McCallum, Minz Won, Sergio Oramas, Erik M. Schmidt:
Mood Classification Using Listening Data. ISMIR 2020: 542-549 - [i13]Filip Korzeniowski, Oriol Nieto, Matthew C. McCallum, Minz Won, Sergio Oramas, Erik M. Schmidt:
Mood Classification Using Listening Data. CoRR abs/2010.11512 (2020)
2010 – 2019
- 2018
- [j2]Matthias Dorfer, Jan Schlüter, Andreu Vall, Filip Korzeniowski, Gerhard Widmer:
End-to-end cross-modality retrieval with CCA projections and pairwise ranking loss. Int. J. Multim. Inf. Retr. 7(2): 117-128 (2018) - [c14]Filip Korzeniowski, Gerhard Widmer:
Automatic Chord Recognition with Higher-Order Harmonic Language Modelling. EUSIPCO 2018: 1900-1904 - [c13]Filip Korzeniowski, David R. W. Sears, Gerhard Widmer:
A Large-Scale Study of Language Models for Chord Prediction. ICASSP 2018: 91-95 - [c12]Filip Korzeniowski, Gerhard Widmer:
Improved Chord Recognition by Combining Duration and Harmonic Language Models. ISMIR 2018: 10-17 - [c11]David R. W. Sears, Filip Korzeniowski, Gerhard Widmer:
Evaluating Language Models of Tonal Harmony. ISMIR 2018: 211-217 - [c10]Filip Korzeniowski, Gerhard Widmer:
Genre-Agnostic Key Classification With Convolutional Neural Networks. ISMIR 2018: 264-270 - [i12]Filip Korzeniowski, David R. W. Sears, Gerhard Widmer:
A Large-Scale Study of Language Models for Chord Prediction. CoRR abs/1804.01849 (2018) - [i11]David R. W. Sears, Filip Korzeniowski, Gerhard Widmer:
Evaluating language models of tonal harmony. CoRR abs/1806.08724 (2018) - [i10]Filip Korzeniowski, Gerhard Widmer:
Improved Chord Recognition by Combining Duration and Harmonic Language Models. CoRR abs/1808.05335 (2018) - [i9]Filip Korzeniowski, Gerhard Widmer:
Genre-Agnostic Key Classification With Convolutional Neural Networks. CoRR abs/1808.05340 (2018) - [i8]Filip Korzeniowski, Gerhard Widmer:
Automatic Chord Recognition with Higher-Order Harmonic Language Modelling. CoRR abs/1808.05341 (2018) - 2017
- [c9]Filip Korzeniowski, Gerhard Widmer:
End-to-end musical key estimation using a convolutional neural network. EUSIPCO 2017: 966-970 - [c8]Filip Korzeniowski, Gerhard Widmer:
On the Futility of Learning Complex Frame-Level Language Models for Chord Recognition. Semantic Audio 2017 - [i7]Filip Korzeniowski, Gerhard Widmer:
On the Futility of Learning Complex Frame-Level Language Models for Chord Recognition. CoRR abs/1702.00178 (2017) - [i6]Matthias Dorfer, Jan Schlüter, Andreu Vall, Filip Korzeniowski, Gerhard Widmer:
End-to-End Cross-Modality Retrieval with CCA Projections and Pairwise Ranking Loss. CoRR abs/1705.06979 (2017) - [i5]Filip Korzeniowski, Gerhard Widmer:
End-to-End Musical Key Estimation Using a Convolutional Neural Network. CoRR abs/1706.02921 (2017) - 2016
- [c7]Filip Korzeniowski, Gerhard Widmer:
Feature Learning for Chord Recognition: The Deep Chroma Extractor. ISMIR 2016: 37-43 - [c6]Rainer Kelz, Matthias Dorfer, Filip Korzeniowski, Sebastian Böck, Andreas Arzt, Gerhard Widmer:
On the Potential of Simple Framewise Approaches to Piano Transcription. ISMIR 2016: 475-481 - [c5]Filip Korzeniowski, Gerhard Widmer:
A fully convolutional deep auditory model for musical chord recognition. MLSP 2016: 1-6 - [c4]Sebastian Böck, Filip Korzeniowski, Jan Schlüter, Florian Krebs, Gerhard Widmer:
madmom: A New Python Audio and Music Signal Processing Library. ACM Multimedia 2016: 1174-1178 - [i4]Sebastian Böck, Filip Korzeniowski, Jan Schlüter, Florian Krebs, Gerhard Widmer:
madmom: a new Python Audio and Music Signal Processing Library. CoRR abs/1605.07008 (2016) - [i3]Filip Korzeniowski, Gerhard Widmer:
Feature Learning for Chord Recognition: The Deep Chroma Extractor. CoRR abs/1612.05065 (2016) - [i2]Filip Korzeniowski, Gerhard Widmer:
A Fully Convolutional Deep Auditory Model for Musical Chord Recognition. CoRR abs/1612.05082 (2016) - [i1]Rainer Kelz, Matthias Dorfer, Filip Korzeniowski, Sebastian Böck, Andreas Arzt, Gerhard Widmer:
On the Potential of Simple Framewise Approaches to Piano Transcription. CoRR abs/1612.05153 (2016) - 2014
- [c3]Florian Krebs, Filip Korzeniowski, Maarten Grachten, Gerhard Widmer:
Unsupervised learning and refinement of rhythmic patterns for beat and downbeat tracking. EUSIPCO 2014: 611-615 - [c2]Filip Korzeniowski, Sebastian Böck, Gerhard Widmer:
Probabilistic Extraction of Beat Positions from a Beat Activation Function. ISMIR 2014: 513-518 - 2013
- [c1]Filip Korzeniowski, Florian Krebs, Andreas Arzt, Gerhard Widmer:
Tracking rests and Tempo changes: Improved Score following with Particle filters. ICMC 2013 - 2012
- [j1]Volkmar Wieser, Clemens Grelck, Peter Haslinger, Jing Guo, Filip Korzeniowski, Robert Bernecky, Bernhard Moser, Sven-Bodo Scholz:
Combining high productivity and high performance in image processing using Single Assignment C on multi-core CPUs and many-core GPUs. J. Electronic Imaging 21(2): 021116 (2012)
Coauthor Index
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