Gerhard Widmer 个人学术档案

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	总计	2019 年至今
引用	18604	6862
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Markus SchedlProfessor at Johannes Kepler University Linz, Institute of Computational Perception在 jku.at 的电子邮件经过验证
Peter KneesFaculty of Informatics, TU Wien在 tuwien.ac.at 的电子邮件经过验证
Elias PampalkNuance Communications在 nuance.com 的电子邮件经过验证
Andreas ArztApple在 apple.com 的电子邮件经过验证
Simon DixonCentre for Digital Music, Queen Mary University of London在 qmul.ac.uk 的电子邮件经过验证
Sebastian BöckNXAI在 nx-ai.com 的电子邮件经过验证
Maarten GrachtenIndependent Machine Learning Consultant在 grachten.eu 的电子邮件经过验证
Werner GoeblProfessor, Head of Department of Music Acoustics, mdw – University of Music and Performing Arts在 mdw.ac.at 的电子邮件经过验证
Arthur FlexerJohannes Kepler University Linz在 jku.at 的电子邮件经过验证
Filip KorzeniowskiMoises.AI在 superfuzz.me 的电子邮件经过验证
Florian KrebsJoanneum Research Graz在 joanneum.at 的电子邮件经过验证
Dominik SchnitzerAustrian Research Institute for Artificial Intelligence (OFAI)在 ofai.at 的电子邮件经过验证
Jan SchlüterJohannes Kepler University Linz (JKU)在 jku.at 的电子邮件经过验证
Carlos Eduardo Cancino-ChacónJohannes Kepler University Linz在 jku.at 的电子邮件经过验证
Fabien GouyonPandora在 pandora.com 的电子邮件经过验证
Andreu VallPumas-AI在 pumas.ai 的电子邮件经过验证
Harald FrostelDepartment for Computational Perception, Johannes Kepler University, Linz, Austria在 jku.at 的电子邮件经过验证
Richard VoglFaculty of Informatics, TU Wien在 tuwien.ac.at 的电子邮件经过验证
Stefan KramerProfessor of Computer Science, Johannes Gutenberg University Mainz在 informatik.uni-mainz.de 的电子邮件经过验证
Xavier SerraDepartment of Information and Communication Technologies, Universitat Pompeu Fabra (UPF), Barcelona在 upf.edu 的电子邮件经过验证

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Gerhard Widmer

Professor of Computer Science, Johannes Kepler University Linz

在 jku.at 的电子邮件经过验证 - 首页

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


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Learning in the presence of concept drift and hidden contexts G Widmer, M Kubat Machine learning 23, 69-101, 1996	2506	1996
Incremental reduced error pruning J Fürnkranz, G Widmer Machine learning proceedings 1994, 70-77, 1994	585	1994
Improvements of Audio-Based Music Similarity and Genre Classificaton. E Pampalk, A Flexer, G Widmer ISMIR 5, 634-637, 2005	350	2005
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	319	2004
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	313	2016
Effective learning in dynamic environments by explicit context tracking G Widmer, M Kubat Machine Learning: ECML-93: European Conference on Machine Learning Vienna …, 1993	262	1993
MATCH: A Music Alignment Tool Chest. S Dixon, G Widmer ISMIR, 492-497, 2005	236	2005
Dynamic Playlist Generation Based on Skipping Behavior. E Pampalk, T Pohle, G Widmer ISMIR 5, 634-637, 2005	225	2005
Exploring music collections by browsing different views E Pampalk, S Dixon, G Widmer Computer Music Journal 28 (2), 49-62, 2004	212	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
Towards Characterisation of Music via Rhythmic Patterns. S Dixon, F Gouyon, G Widmer ISMIR, 2004	204	2004
Efficient training of audio transformers with patchout K Koutini, J Schlüter, H Eghbal-Zadeh, G Widmer arXiv preprint arXiv:2110.05069, 2021	199	2021
Prediction of ordinal classes using regression trees S Kramer, G Widmer, B Pfahringer, M De Groeve Fundamenta Informaticae 47 (1), 1-13, 2001	196	2001
Tracking context changes through meta-learning G Widmer Machine learning 27, 259-286, 1997	192	1997
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	180	2016
Maximum filter vibrato suppression for onset detection S Böck, G Widmer Proc. of the 16th Int. Conf. on Digital Audio Effects (DAFx). Maynooth …, 2013	180	2013
Deep linear discriminant analysis M Dorfer, R Kelz, G Widmer arXiv preprint arXiv:1511.04707, 2015	170	2015
Classification of dance music by periodicity patterns S Dixon, E Pampalk, G Widmer Johns Hopkins University, 2003	166	2003

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