Rebecca Fiebrink

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Ge WangAssociate Professor of Music (also Computer Science), Stanford UniversityVerified email at ccrma.stanford.edu
Spencer SalazarPrincipal Engineer, Output Inc.Verified email at ccrma.stanford.edu
Marco GilliesProfessor in Computing, Goldsmiths, University of LondonVerified email at gold.ac.uk
Michael ZbyszyńskiVerified email at mikezed.com
Baptiste CaramiauxCNRS researcher (HDR), ISIR, Sorbonne UniversitéVerified email at lri.fr
Ichiro FujinagaProfessor, Music Technology Area, Schulich School of Music, McGill UniversityVerified email at mcgill.ca
Memo AktenGoldsmiths, University of LondonVerified email at msavisuals.com
Francisco BernardoResearch Associate in Digital Musical Instrument Design, Imperial College LondonVerified email at imperial.ac.uk
Reid OdaPrinceton UniversityVerified email at princeton.edu
Atau TanakaGoldsmiths, University of LondonVerified email at goldsmithsdigital.com
Annie KellyUniversity of Colorado BoulderVerified email at colorado.edu
Marcelo M. WanderleyProfessor, Music Technology - McGill UniversityVerified email at mcgill.ca
Joseph MallochAssistant Professor, Dalhousie UniversityVerified email at dal.ca
Cory McKayProfessor of Music, Marianopolis CollegeVerified email at mail.mcgill.ca
Dan MorrisResearch Scientist, Google AI for Nature and SocietyVerified email at cs.stanford.edu
Hugo Scurtoartist, designer & researcher* (PhD)Verified email at hugoscurto.com
margaret schedelStony Brook UniversityVerified email at stonybrook.edu
Meredith Ringel MorrisDirector, Human-AI Interaction Research, Google DeepMindVerified email at google.com
Zafer BarutcuogluPh.D. in Computer Science, Princeton UniversityVerified email at cs.princeton.edu
Christopher DeCoroPh.D. in Computer Science, Princeton UniversityVerified email at cs.princeton.edu

Rebecca Fiebrink

Professor, Creative Computing Institute, University of the Arts London

Verified email at arts.ac.uk - Homepage

Human-computer interaction machine learning technologies for music and creative expression


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Human model evaluation in interactive supervised learning R Fiebrink, PR Cook, D Trueman Proceedings of the SIGCHI conference on human factors in computing systems …, 2011	221	2011
A meta-instrument for interactive, on-the-fly machine learning R Fiebrink, D Trueman, PR Cook International Conference on New Interfaces for Musical Expression (NIME), 2009	181	2009
Human-centred machine learning M Gillies, R Fiebrink, A Tanaka, J Garcia, F Bevilacqua, A Heloir, ... Proceedings of the 2016 CHI conference extended abstracts on human factors …, 2016	177	2016
Real-time human interaction with supervised learning algorithms for music composition and performance RA Fiebrink Princeton University, 2011	169	2011
2005: Towards a Dimension Space for Musical Devices D Birnbaum, R Fiebrink, J Malloch, MM Wanderley A NIME Reader: Fifteen Years of New Interfaces for Musical Expression, 211-222, 2017	153	2017
The Wekinator: a system for real-time, interactive machine learning in music R Fiebrink, PR Cook Proceedings of The Eleventh International Society for Music Information …, 2010	145	2010
Mixed-initiative creative interfaces S Deterding, J Hook, R Fiebrink, M Gillies, J Gow, M Akten, G Smith, ... Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors …, 2017	111	2017
Machine learning education for artists, musicians, and other creative practitioners R Fiebrink ACM Transactions on Computing Education (TOCE) 19 (4), 1-32, 2019	101	2019
The machine learning algorithm as creative musical tool R Fiebrink, B Caramiaux arXiv preprint arXiv:1611.00379, 2016	100	2016
Don't forget the laptop: using native input capabilities for expressive musical control R Fiebrink, G Wang, PR Cook Proceedings of the 7th international conference on New interfaces for …, 2007	89	2007
Continuous score-coded pitch correction S Salazar, RA Fiebrink, G Wang, M Ljungström, JC Smith, PR Cook US Patent 9,147,385, 2015	79	2015
From rituals to magic: Interactive art and HCI of the past, present, and future M Jeon, R Fiebrink, EA Edmonds, D Herath International Journal of Human-Computer Studies 131, 108-119, 2019	76	2019
Bayesian Aggregation for Hierarchical Genre Classification. C DeCoro, Z Barutcuoglu, R Fiebrink ISMIR, 77-80, 2007	74	2007
How machine learning impacts the undergraduate computing curriculum RB Shapiro, R Fiebrink, P Norvig Communications of the ACM 61 (11), 27-29, 2018	67	2018
ACE: A Framework for Optimizing Music Classification. C McKay, R Fiebrink, D McEnnis, B Li, I Fujinaga ISMIR, 42-49, 2005	65	2005
Using interactive machine learning to support interface development through workshops with disabled people S Katan, M Grierson, R Fiebrink Proceedings of the 33rd annual ACM conference on human factors in computing …, 2015	64	2015
Toward understanding human-computer interaction in composing the instrument R Fiebrink, D Trueman, NC Britt, M Nagai, K Kaczmarek, M Early, ... ICMC, 2010	62	2010
World stage for pitch-corrected vocal performances S Salazar, RA Fiebrink, G Wang, M Ljungström, JC Smith, J Yang US Patent 8,682,653, 2014	59	2014
Feature Selection Pitfalls and Music Classification. R Fiebrink, I Fujinaga ISMIR, 340-341, 2006	55	2006
Dynamic mapping of physical controls for tabletop groupware R Fiebrink, D Morris, MR Morris Proceedings of the SIGCHI Conference on Human Factors in Computing Systems …, 2009	49	2009

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