Kat Agres
Citado por
Citado por
Information‐Theoretic Properties of Auditory Sequences Dynamically Influence Expectation and Memory
K Agres, S Abdallah, M Pearce
Cognitive Science, 1-34, 2017
Evaluation of musical creativity and musical metacreation systems
K Agres, J Forth, GA Wiggins
Computers in Entertainment (CIE) 14 (3), 1-33, 2016
From Distributional Semantics to Conceptual Spaces: A Novel Computational Method for Concept Creation
S McGregor, K Agres, M Purver, G & Wiggins
Journal of Artificial General Intelligence 6 (1), 55–86, 2015
Musical expectancy: The influence of musical structure on emotional response
CL Krumhansl, KR Agres
Behavioral and Brain Sciences 31 (5), 584, 2008
Musical change deafness: The inability to detect change in a non-speech auditory domain
KR Agres, CL Krumhansl
Proceedings of the 30th annual conference of the cognitive science society …, 2008
Meta4meaning: Automatic metaphor interpretation using corpus-derived word associations
P Xiao, K Alnajjar, M Granroth-Wilding, K Agres, H Toivonen
Proceedings of the Seventh International Conference on Computational Creativity, 2016
Entraining IDyOT: timing in the information dynamics of thinking
J Forth, K Agres, M Purver, GA Wiggins
Frontiers in psychology 7, 1575, 2016
Modeling metaphor perception with distributional semantics vector space models.
KR Agres, S McGregor, K Rataj, M Purver, GA Wiggins
C3GI@ ESSLLI, 2016
Conceptualizing Creativity: From Distributional Semantics to Conceptual Spaces.
K Agres, S McGregor, M Purver, GA Wiggins
ICCC, 118-125, 2015
Mixed-curvature Variational Autoencoders
O Skopek, OE Ganea, G Bécigneul
arXiv preprint arXiv:1911.08411, 2019
Harmonic Structure Predicts the Enjoyment of Uplifting Trance Music
K Agres, D Herremans, L Bigo, D Conklin
Frontiers in Psychology: Cognitive Science 7, 2017
Learning disentangled representations of timbre and pitch for musical instrument sounds using gaussian mixture variational autoencoders
YJ Luo, K Agres, D Herremans
arXiv preprint arXiv:1906.08152, 2019
A closed-loop, music-based brain-computer interface for emotion mediation
SK Ehrlich, KR Agres, C Guan, G Cheng
PloS one 14 (3), e0213516, 2019
Probabilistic segmentation of musical sequences using restricted Boltzmann machines
S Lattner, M Grachten, K Agres, CEC Chacón
International Conference on Mathematics and Computation in Music, 323-334, 2015
Intelligibility of Sung Lyrics: A Pilot Study.
KM Ibrahim, D Grunberg, K Agres, C Gupta, Y Wang
ISMIR, 686-693, 2017
The sparsity of simple recurrent networks in musical structure learning
KR Agres, JE DeLong, M Spivey
Proceedings of the Annual Meeting of the Cognitive Science Society 31 (31), 2009
Singing voice conversion with disentangled representations of singer and vocal technique using variational autoencoders
YJ Luo, CC Hsu, K Agres, D Herremans
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
An Information-Theoretic Account of Musical Expectation and Memory
K Agres, S Abdallah, M Pearce
Proceedings of the 35th Annual Conference of the Cognitive Science Society …, 2013
From context to concept: exploring semantic relationships in music with word2vec
CH Chuan, K Agres, D Herremans
Neural Computing and Applications 32 (4), 1023-1036, 2020
From Bach to the Beatles: The simulation of human tonal expectation using ecologically-trained predictive models
C Cancino-Chacón, M Grachten, K Agres
arXiv preprint arXiv:1707.06231, 2017
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Artículos 1–20