Geraint Wiggins
Geraint Wiggins
Professor of Computational Creativity, Vrije Universiteit Brussel / Queen Mary University of London
Bestätigte E-Mail-Adresse bei vub.ac.be
TitelZitiert vonJahr
A preliminary framework for description, analysis and comparison of creative systems
GA Wiggins
Knowledge-Based Systems 19 (7), 449-458, 2006
2972006
Computational creativity: The final frontier?
S Colton, GA Wiggins
Ecai 12, 21-26, 2012
2732012
Expectation in melody: The influence of context and learning
MT Pearce, GA Wiggins
Music Perception 23 (5), 377-405, 2006
2642006
AI methods for algorithmic composition: A survey, a critical view and future prospects
G Papadopoulos, G Wiggins
AISB Symposium on Musical Creativity 124, 110-117, 1999
2471999
Algorithms for discovering repeated patterns in multidimensional representations of polyphonic music
D Meredith, K Lemström, GA Wiggins
Journal of New Music Research 31 (4), 321-345, 2002
1992002
Unsupervised statistical learning underpins computational, behavioural, and neural manifestations of musical expectation
MT Pearce, MH Ruiz, S Kapasi, GA Wiggins, J Bhattacharya
NeuroImage 50 (1), 302-313, 2010
1842010
Searching for computational creativity
GA Wiggins
New Generation Computing 24 (3), 209-222, 2006
1642006
Musical creativity: multidisciplinary research in theory and practice
I Delège, GA Wiggins
Psychology Press, 2006
1382006
Evolutionary methods for musical composition
G Wiggins, G Papadopoulos, S Phon-Amnuaisuk, A Tuson
ICANNGA, 1998
1351998
Improved methods for statistical modelling of monophonic music
M Pearce, G Wiggins
Journal of New Music Research 33 (4), 367-385, 2004
1312004
Auditory expectation: the information dynamics of music perception and cognition
MT Pearce, GA Wiggins
Topics in cognitive science 4 (4), 625-652, 2012
1252012
Statistical learning of harmonic movement
D Ponsford, G Wiggins, C Mellish
Journal of New Music Research 28 (2), 150-177, 1999
1121999
A framework for the evaluation of music representation systems
G Wiggins, E Miranda, A Smaill, M Harris
Computer Music Journal 17 (3), 31-42, 1993
1111993
A genetic algorithm for the generation of jazz melodies
G Papadopoulos, G Wiggins
Proceedings of STEP 98, 1998
1071998
Probabilistic models of expectation violation predict psychophysiological emotional responses to live concert music
H Egermann, MT Pearce, GA Wiggins, S McAdams
Cognitive, Affective, & Behavioral Neuroscience 13 (3), 533-553, 2013
1012013
Towards a framework for the evaluation of machine compositions
M Pearce, G Wiggins
Proceedings of the AISB’01 Symposium on Artificial Intelligence and …, 2001
962001
The four-part harmonisation problem: a comparison between genetic algorithms and a rule-based system
S Phon-Amnuaisuk, GA Wiggins
Proceedings of the AISB’99 Symposium on Musical Creativity, 28-34, 1999
941999
Motivations and methodologies for automation of the compositional process
M Pearce, D Meredith, G Wiggins
Musicae Scientiae 6 (2), 119-147, 2002
882002
Converging on the divergent: The history (and future) of the international joint workshops in computational creativity
A Cardoso, T Veale, GA Wiggins
AI Magazine 30 (3), 15-15, 2009
852009
The role of expectation and probabilistic learning in auditory boundary perception: A model comparison
MT Pearce, D Müllensiefen, GA Wiggins
Perception 39 (10), 1367-1391, 2010
822010
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