| Computational creativity: The final frontier? S Colton, GA Wiggins ECAI 2012, 21-26, 2012 | 849 | 2012 |
| A preliminary framework for description, analysis and comparison of creative systems GA Wiggins Knowledge-based systems 19 (7), 449-458, 2006 | 523 | 2006 |
| Expectation in melody: The influence of context and learning MT Pearce, GA Wiggins Music Perception 23 (5), 377-405, 2006 | 389 | 2006 |
| 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 | 348 | 1999 |
| Auditory expectation: the information dynamics of music perception and cognition MT Pearce, GA Wiggins Topics in cognitive science 4 (4), 625-652, 2012 | 318 | 2012 |
| 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 | 310 | 2010 |
| 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 | 306 | 2002 |
| Searching for computational creativity GA Wiggins New Generation Computing 24 (3), 209-222, 2006 | 282 | 2006 |
| 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 | 251 | 2013 |
| Musical creativity: multidisciplinary research in theory and practice I Delège, GA Wiggins Psychology Press, 2006 | 243 | 2006 |
| Improved methods for statistical modelling of monophonic music M Pearce, G Wiggins Journal of New Music Research 33 (4), 367-385, 2004 | 183 | 2004 |
| 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 | 153 | 2010 |
| Evolutionary methods for musical composition G Wiggins, G Papadopoulos, S Phon-Amnuaisuk, A Tuson ICANNGA, 1998 | 150 | 1998 |
| 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 | 148 | 1993 |
| A genetic algorithm for the generation of jazz melodies G Wiggins, G Papadopoulos Proceedings of the finnish conference on artificial intelligence (STeP’98 …, 1998 | 142* | 1998 |
| Statistical learning of harmonic movement D Ponsford, G Wiggins, C Mellish Journal of New Music Research 28 (2), 150-177, 1999 | 135 | 1999 |
| Motivations and methodologies for automation of the compositional process M Pearce, D Meredith, G Wiggins Musicae Scientiae 6 (2), 119-147, 2002 | 132 | 2002 |
| 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 | 131 | 2009 |
| Towards a framework for the evaluation of machine compositions M Pearce, G Wiggins Proceedings of the AISB 1, 22-32, 2001 | 125 | 2001 |
| The four-part harmonisation problem: a comparison between genetic algorithms and a rule-based system S Phon-Amnuaisuk, G Wiggins Proceedings of the AISB’99 Symposium on Musical Creativity, 28-34, 1999 | 110 | 1999 |
Marcus PearceQueen Mary University of LondonVerified email at qmul.ac.uk
