Gerhard Widmer

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Markus SchedlProfessor at Johannes Kepler University Linz, Institute of Computational PerceptionVerified email at jku.at
Peter KneesFaculty of Informatics, TU WienVerified email at tuwien.ac.at
Elias PampalkMicrosoftVerified email at microsoft.com
Andreas ArztAppleVerified email at apple.com
Simon DixonCentre for Digital Music, Queen Mary University of LondonVerified email at qmul.ac.uk
Sebastian BöckNXAIVerified email at nx-ai.com
Maarten GrachtenIndependent Machine Learning ConsultantVerified email at grachten.eu
Werner GoeblProfessor, Head of Department of Music Acoustics, mdw – University of Music and Performing ArtsVerified email at mdw.ac.at
Arthur FlexerJohannes Kepler University LinzVerified email at jku.at
Filip KorzeniowskiMoises.AIVerified email at superfuzz.me
Florian KrebsJoanneum Research GrazVerified email at joanneum.at
Dominik SchnitzerAustrian Research Institute for Artificial Intelligence (OFAI)Verified email at ofai.at
Jan SchlüterJohannes Kepler University Linz (JKU)Verified email at jku.at
Carlos Eduardo Cancino-ChacónJohannes Kepler University LinzVerified email at jku.at
Fabien GouyonPandoraVerified email at pandora.com
Andreu VallPumasAIVerified email at pumas.ai
Harald FrostelDepartment for Computational Perception, Johannes Kepler University, Linz, AustriaVerified email at jku.at
Richard VoglFaculty of Informatics, TU WienVerified email at tuwien.ac.at
Xavier SerraDepartment of Information and Communication Technologies, Universitat Pompeu Fabra (UPF), BarcelonaVerified email at upf.edu
Stefan KramerProfessor of Computer Science, Johannes Gutenberg University MainzVerified email at informatik.uni-mainz.de

Gerhard Widmer

Professor of Computer Science, Johannes Kepler University Linz

Verified email at jku.at - Homepage

Artificial Intelligence Machine Learning Sound and Music Computing Music Information Retrieval Computational Musicology


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Learning in the presence of concept drift and hidden contexts G Widmer, M Kubat Machine learning 23, 69-101, 1996	2542	1996
Incremental reduced error pruning J Fürnkranz, G Widmer Machine learning proceedings 1994, 70-77, 1994	593	1994
Improvements of Audio-Based Music Similarity and Genre Classificaton. E Pampalk, A Flexer, G Widmer ISMIR 5, 634-637, 2005	352	2005
Madmom: A new python audio and music signal processing library S Böck, F Korzeniowski, J Schlüter, F Krebs, G Widmer Proceedings of the 24th ACM international conference on Multimedia, 1174-1178, 2016	326	2016
Computational models of expressive music performance: The state of the art G Widmer, W Goebl Journal of new music research 33 (3), 203-216, 2004	322	2004
Effective learning in dynamic environments by explicit context tracking G Widmer, M Kubat Machine Learning: ECML-93: European Conference on Machine Learning Vienna …, 1993	264	1993
Efficient training of audio transformers with patchout K Koutini, J Schlüter, H Eghbal-Zadeh, G Widmer arXiv preprint arXiv:2110.05069, 2021	242	2021
MATCH: A Music Alignment Tool Chest. S Dixon, G Widmer ISMIR, 492-497, 2005	242	2005
Dynamic Playlist Generation Based on Skipping Behavior. E Pampalk, T Pohle, G Widmer ISMIR 5, 634-637, 2005	228	2005
Exploring music collections by browsing different views E Pampalk, S Dixon, G Widmer Computer Music Journal 28 (2), 49-62, 2004	214	2004
Towards Characterisation of Music via Rhythmic Patterns. S Dixon, F Gouyon, G Widmer ISMIR, 2004	206	2004
Evaluating rhythmic descriptors for musical genre classification F Gouyon, S Dixon, E Pampalk, G Widmer Proceedings of the AES 25th International Conference 196, 204, 2004	206	2004
CP-JKU submissions for DCASE-2016: a hybrid approach using binaural i-vectors and deep convolutional neural networks H Eghbal-Zadeh, B Lehner, M Dorfer, G Widmer IEEE AASP Challenge on Detection and Classification of Acoustic Scenes and …, 2016	205	2016
Prediction of ordinal classes using regression trees S Kramer, G Widmer, B Pfahringer, M De Groeve Fundamenta Informaticae 47 (1), 1-13, 2001	198	2001
Tracking context changes through meta-learning G Widmer Machine learning 27, 259-286, 1997	193	1997
Maximum filter vibrato suppression for onset detection S Böck, G Widmer Proc. of the 16th Int. Conf. on Digital Audio Effects (DAFx). Maynooth …, 2013	191	2013
Machine discoveries: A few simple, robust local expression principles G Widmer Journal of New Music Research 31 (1), 37-50, 2002	190	2002
Joint Beat and Downbeat Tracking with Recurrent Neural Networks. S Böck, F Krebs, G Widmer ISMIR, 255-261, 2016	188	2016
Deep linear discriminant analysis M Dorfer, R Kelz, G Widmer arXiv preprint arXiv:1511.04707, 2015	175	2015
Playlist Generation using Start and End Songs. A Flexer, D Schnitzer, M Gasser, G Widmer ISMIR 8, 173-178, 2008	169	2008

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