| Computational models of expressive music performance: A comprehensive and critical review CE Cancino-Chacón, M Grachten, W Goebl, G Widmer Frontiers in Digital Humanities 5, 25, 2018 | 66 | 2018 |
| An evaluation of linear and non-linear models of expressive dynamics in classical piano and symphonic music CE Cancino-Chacón, T Gadermaier, G Widmer, M Grachten Machine Learning 106, 887-909, 2017 | 51 | 2017 |
| Moving to communicate, moving to interact: Patterns of body motion in musical duo performance L Bishop, C Cancino-Chacón, W Goebl Music Perception: An Interdisciplinary Journal 37 (1), 1-25, 2019 | 50 | 2019 |
| Eye gaze as a means of giving and seeking information during musical interaction L Bishop, C Cancino-Chacón, W Goebl Consciousness and cognition 68, 73-96, 2019 | 34 | 2019 |
| Composer recognition based on 2D-filtered piano-rolls G Velarde, T Weyde, CC Chacón, D Meredith, M Grachten International Society for Music Information Retrieval Conference, 115-121, 2016 | 23 | 2016 |
| A convolutional approach to melody line identification in symbolic scores F Simonetta, C Cancino-Chacón, S Ntalampiras, G Widmer arXiv preprint arXiv:1906.10547, 2019 | 21 | 2019 |
| Convolution-based classification of audio and symbolic representations of music G Velarde, C Cancino Chacón, D Meredith, T Weyde, M Grachten Journal of New Music Research 47 (3), 191-205, 2018 | 18 | 2018 |
| Partitura: A python package for symbolic music processing C Cancino-Chacón, SD Peter, E Karystinaios, F Foscarin, M Grachten, ... arXiv preprint arXiv:2206.01071, 2022 | 17 | 2022 |
| Probabilistic Segmentation of Musical Sequences using Restricted Boltzmann Machines S Lattner, M Grachten, K Agres, CE Cancino Chacón Mathematics and Computation in Music, 323-334, 2015 | 17 | 2015 |
| An evaluation of score descriptors combined with non-linear models of expressive dynamics in music CE Cancino Chacón, M Grachten International Conference on Discovery Science, 48-62, 2015 | 16 | 2015 |
| Computational Modeling of Expressive Music Performance with Linear and Non-linear Basis Function Models CE Cancino-Chacón Johannes Kepler University Linz, 2018 | 14 | 2018 |
| THE BASIS MIXER: A COMPUTATIONAL ROMANTIC PIANIST CE Cancino Chacón, M Grachten | 14* | |
| Strategies for Conceptual Change in Convolutional Neural Networks M Grachten, CE Cancino Chacón | 12 | 2015 |
| Least squares phase estimation of mixed signals. CE Cancino Chacón, P Mowlaee INTERSPEECH, 2705-2709, 2014 | 12 | 2014 |
| The match file format: Encoding Alignments between Scores and Performances F Foscarin, E Karystinaios, SD Peter, C Cancino-Chacón, M Grachten, ... arXiv preprint arXiv:2206.01104, 2022 | 11 | 2022 |
| Temporal dependencies in the expressive timing of classical piano performances M Grachten, CEC Chacón The routledge companion to embodied music interaction, 360-369, 2017 | 11 | 2017 |
| Toward computer-assisted understanding of dynamics in symphonic music M Grachten, CE Cancino-Chacón, T Gadermaier, G Widmer IEEE MultiMedia 24 (1), 36-46, 2017 | 11 | 2017 |
| Developing Tonal Perception through Unsupervised Learning. CE Cancino Chacón, S Lattner, M Grachten ISMIR, 195-200, 2014 | 11 | 2014 |
| The ACCompanion v0. 1: An expressive accompaniment system C Cancino-Chacón, M Bonev, A Durand, M Grachten, A Arzt, L Bishop, ... arXiv preprint arXiv:1711.02427, 2017 | 10 | 2017 |
| On the characterization of expressive performance in classical music: First results of the con espressione game C Cancino-Chacón, S Peter, S Chowdhury, A Aljanaki, G Widmer arXiv preprint arXiv:2008.02194, 2020 | 9 | 2020 |
Maarten GrachtenIndependent Machine Learning Consultant在 grachten.eu 的电子邮件经过验证
