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Maarten Grachten
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2020 – today
- 2024
- [c31]Marco Pasini, Maarten Grachten, Stefan Lattner:
Bass Accompaniment Generation Via Latent Diffusion. ICASSP 2024: 1166-1170 - [i21]Marco Pasini, Maarten Grachten, Stefan Lattner:
Bass Accompaniment Generation via Latent Diffusion. CoRR abs/2402.01412 (2024) - [i20]Maarten Grachten:
Measuring audio prompt adherence with distribution-based embedding distances. CoRR abs/2404.00775 (2024) - [i19]Javier Nistal, Marco Pasini, Cyran Aouameur, Maarten Grachten, Stefan Lattner:
Diff-A-Riff: Musical Accompaniment Co-creation via Latent Diffusion Models. CoRR abs/2406.08384 (2024) - 2023
- [c30]Ali Nikrang
, Maarten Grachten, Martin Gasser, Harald Frostel, Gerhard Widmer
, Tom Collins
:
Music Visualisation and Its Short-Term Effect on Appraisal Skills. HCI (50) 2023: 112-130 - 2022
- [j8]Emmanuel Deruty, Maarten Grachten, Stefan Lattner, Javier Nistal, Cyran Aouameur:
On the Development and Practice of AI Technology for Contemporary Popular Music Production. Trans. Int. Soc. Music. Inf. Retr. 5(1): 35 (2022) - [i18]Maarten Grachten, Carlos Cancino Chacón, Thassilo Gadermaier:
partitura: A Python Package for Handling Symbolic Musical Data. CoRR abs/2201.13144 (2022) - [i17]Carlos Cancino Chacón, Silvan David Peter, Emmanouil Karystinaios, Francesco Foscarin, Maarten Grachten, Gerhard Widmer:
Partitura: A Python Package for Symbolic Music Processing. CoRR abs/2206.01071 (2022) - [i16]Francesco Foscarin, Emmanouil Karystinaios, Silvan David Peter, Carlos Cancino Chacón, Maarten Grachten, Gerhard Widmer:
The match file format: Encoding Alignments between Scores and Performances. CoRR abs/2206.01104 (2022) - [i15]Emmanuel Deruty, Maarten Grachten:
"Melatonin": A Case Study on AI-induced Musical Style. CoRR abs/2208.08968 (2022)
2010 – 2019
- 2019
- [c29]Maarten Grachten, Emmanuel Deruty, Alexandre Tanguy:
Auto-adaptive Resonance Equalization using Dilated Residual Networks. ISMIR 2019: 405-411 - [c28]Stefan Lattner, Maarten Grachten:
High-Level Control of Drum Track Generation Using Learned Patterns of Rhythmic Interaction. WASPAA 2019: 35-39 - [i14]Stefan Lattner, Maarten Grachten:
High-Level Control of Drum Track Generation Using Learned Patterns of Rhythmic Interaction. CoRR abs/1908.00948 (2019) - 2018
- [j7]Carlos Eduardo Cancino Chacón
, Maarten Grachten, Werner Goebl
, Gerhard Widmer:
Computational Models of Expressive Music Performance: A Comprehensive and Critical Review. Frontiers Digit. Humanit. 5: 25 (2018) - [c27]Stefan Lattner, Maarten Grachten, Gerhard Widmer:
A Predictive Model for Music based on Learned Interval Representations. ISMIR 2018: 26-33 - [c26]Stefan Lattner, Maarten Grachten, Gerhard Widmer:
Learning Interval Representations from Polyphonic Music Sequences. ISMIR 2018: 661-668 - [i13]Stefan Lattner, Maarten Grachten, Gerhard Widmer:
Learning Transposition-Invariant Interval Features from Symbolic Music and Audio. CoRR abs/1806.08236 (2018) - [i12]Stefan Lattner, Maarten Grachten, Gerhard Widmer:
A Predictive Model for Music Based on Learned Interval Representations. CoRR abs/1806.08686 (2018) - [i11]Carlos Cancino Chacón, Maarten Grachten:
A Computational Study of the Role of Tonal Tension in Expressive Piano Performance. CoRR abs/1807.01080 (2018) - [i10]Maarten Grachten, Emmanuel Deruty, Alexandre Tanguy:
Auto-adaptive Resonance Equalization using Dilated Residual Networks. CoRR abs/1807.08636 (2018) - 2017
- [j6]Maarten Grachten, Carlos Eduardo Cancino Chacón
, Thassilo Gadermaier
, Gerhard Widmer
:
Toward Computer-Assisted Understanding of Dynamics in Symphonic Music. IEEE Multim. 24(1): 36-46 (2017) - [j5]Carlos Eduardo Cancino Chacón
, Thassilo Gadermaier
, Gerhard Widmer
, Maarten Grachten:
An evaluation of linear and non-linear models of expressive dynamics in classical piano and symphonic music. Mach. Learn. 106(6): 887-909 (2017) - [c25]Carlos Eduardo Cancino Chacón, Maarten Grachten, Kat Agres:
From Bach to the Beatles: The Simulation of Human Tonal Expectation Using Ecologically-Trained Predictive Models. ISMIR 2017: 494-501 - [i9]Stefan Lattner, Maarten Grachten:
Improving Content-Invariance in Gated Autoencoders for 2D and 3D Object Rotation. CoRR abs/1707.01357 (2017) - [i8]Carlos Eduardo Cancino Chacón, Maarten Grachten, Kat Agres:
From Bach to the Beatles: The simulation of human tonal expectation using ecologically-trained predictive models. CoRR abs/1707.06231 (2017) - [i7]Stefan Lattner, Maarten Grachten, Gerhard Widmer:
Learning Musical Relations using Gated Autoencoders. CoRR abs/1708.05325 (2017) - [i6]Carlos Eduardo Cancino Chacón, Maarten Grachten, David R. W. Sears, Gerhard Widmer:
What were you expecting? Using Expectancy Features to Predict Expressive Performances of Classical Piano Music. CoRR abs/1709.03629 (2017) - [i5]Maarten Grachten, Carlos Eduardo Cancino Chacón:
Strategies for Conceptual Change in Convolutional Neural Networks. CoRR abs/1711.01634 (2017) - [i4]Carlos Cancino Chacón, Martin Bonev, Amaury Durand, Maarten Grachten, Andreas Arzt, Laura Bishop, Werner Goebl, Gerhard Widmer:
The ACCompanion v0.1: An Expressive Accompaniment System. CoRR abs/1711.02427 (2017) - 2016
- [c24]Gissel Velarde, Tillman Weyde, Carlos Eduardo Cancino Chacón, David Meredith, Maarten Grachten:
Composer Recognition Based on 2D-Filtered Piano-Rolls. ISMIR 2016: 115-121 - [i3]Maarten Grachten, Carlos Eduardo Cancino Chacón, Thassilo Gadermaier, Gerhard Widmer:
Towards computer-assisted understanding of dynamics in symphonic music. CoRR abs/1612.02198 (2016) - [i2]Stefan Lattner, Maarten Grachten, Gerhard Widmer:
Imposing higher-level Structure in Polyphonic Music Generation using Convolutional Restricted Boltzmann Machines and Constraints. CoRR abs/1612.04742 (2016) - [i1]Thassilo Gadermaier, Maarten Grachten, Carlos Eduardo Cancino Chacón:
Basis-Function Modeling of Loudness Variations in Ensemble Performance. CoRR abs/1612.05432 (2016) - 2015
- [c23]Kat Agres, Carlos Cancino, Maarten Grachten, Stefan Lattner:
A Computational Approach to Modelling the Perception of Pitch and Tonality in Music. CogSci 2015 - [c22]Carlos Eduardo Cancino Chacón
, Maarten Grachten:
An Evaluation of Score Descriptors Combined with Non-linear Models of Expressive Dynamics in Music. Discovery Science 2015: 48-62 - [c21]Andreas Arzt, Harald Frostel, Thassilo Gadermaier, Martin Gasser, Maarten Grachten, Gerhard Widmer:
Artificial Intelligence in the Concertgebouw. IJCAI 2015: 2424-2430 - [c20]Stefan Lattner, Carlos Eduardo Cancino Chacón, Maarten Grachten:
Pseudo-Supervised Training Improves Unsupervised Melody Segmentation. IJCAI 2015: 2459-2465 - [c19]Martin Gasser, Andreas Arzt, Thassilo Gadermaier, Maarten Grachten, Gerhard Widmer:
Classical Music on the Web - User Interfaces and Data Representations. ISMIR 2015: 571-577 - [c18]Stefan Lattner, Maarten Grachten, Kat Agres
, Carlos Eduardo Cancino Chacón
:
Probabilistic Segmentation of Musical Sequences Using Restricted Boltzmann Machines. MCM 2015: 323-334 - 2014
- [j4]Maarten Grachten, Florian Krebs:
An Assessment of Learned Score Features for Modeling Expressive Dynamics in Music. IEEE Trans. Multim. 16(5): 1211-1218 (2014) - [c17]Florian Krebs, Filip Korzeniowski, Maarten Grachten, Gerhard Widmer:
Unsupervised learning and refinement of rhythmic patterns for beat and downbeat tracking. EUSIPCO 2014: 611-615 - [c16]Sam van Herwaarden, Maarten Grachten, W. Bas de Haas:
Predicting Expressive Dynamics in Piano Performances using Neural Networks. ISMIR 2014: 47-52 - [c15]Carlos Eduardo Cancino Chacón, Stefan Lattner, Maarten Grachten:
Developing Tonal Perception through Unsupervised Learning. ISMIR 2014: 195-200 - 2013
- [c14]Maarten Grachten, Martin Gasser, Andreas Arzt, Gerhard Widmer:
Automatic Alignment of Music Performances with Structural Differences. ISMIR 2013: 607-612 - [p1]Sebastian Flossmann, Maarten Grachten, Gerhard Widmer:
Expressive Performance Rendering with Probabilistic Models. Guide to Computing for Expressive Music Performance 2013: 75-98 - 2012
- [j3]Denis Amelynck, Maarten Grachten, Leon van Noorden, Marc Leman:
Toward E-Motion-Based Music Retrieval a Study of Affective Gesture Recognition. IEEE Trans. Affect. Comput. 3(2): 250-259 (2012) - 2010
- [c13]Miguel Molina-Solana, Maarten Grachten, Gerhard Widmer:
Evidence for Pianist-specific Rubato Style in Chopin Nocturnes. ISMIR 2010: 225-230
2000 – 2009
- 2009
- [j2]Gerhard Widmer
, Sebastian Flossmann, Maarten Grachten:
YQX Plays Chopin. AI Mag. 30(3): 35-48 (2009) - [c12]Maarten Grachten, Gerhard Widmer:
Who Is Who in the End? Recognizing Pianists by Their Final Ritardandi. ISMIR 2009: 51-56 - [c11]Maarten Grachten, Markus Schedl, Tim Pohle, Gerhard Widmer:
The ISMIR Cloud: A Decade of ISMIR Conferences at Your Fingertips. ISMIR 2009: 63-68 - 2007
- [c10]Ramón López de Mántaras, Maarten Grachten, Josep Lluís Arcos:
Playing with Cases: Tempo Transformations of Jazz Performances Using Case-Based Reasoning. FLAIRS 2007: 8-11 - 2006
- [b1]Maarten Grachten:
Expressivity-aware tempo transformations of music performances using case based reasoning. Pompeu Fabra University, Spain, 2006 - [j1]Maarten Grachten, Josep Lluís Arcos
, Ramón López de Mántaras:
A case based approach to expressivity-aware tempo transformation. Mach. Learn. 65(2-3): 411-437 (2006) - [c9]Maarten Grachten, Josep Lluís Arcos, Ramón López de Mántaras:
TempoExpress: An Expressivity-Preserving Musical Tempo Transformation System. AAAI 2006: 1609-1612 - [c8]Amaury Hazan, Maarten Grachten, Rafael Ramírez:
Evolving Performance Models by Performance Similarity: Beyond Note-to-note Transformations. ISMIR 2006: 67-72 - [c7]Ramón López de Mántaras, Maarten Grachten, Josep Lluís Arcos:
Expressivity-Preserving Tempo Transformation for Music - A Case-Based Approach. KI 2006: 1-6 - 2005
- [c6]Maarten Grachten, F. Alejandro García, Josep Lluís Arcos:
Navigating Through Case Base Competence. ICCBR 2005: 282-295 - 2004
- [c5]Maarten Grachten, Josep Lluís Arcos, Ramón López de Mántaras:
Evolutionary Optimization of Music Performance Annotation. CMMR 2004: 347-358 - [c4]Maarten Grachten, Josep Lluís Arcos:
Using the Implication/Realization Model for Measuring Melodic Similarity. ECAI 2004: 1023-1024 - [c3]Maarten Grachten, Josep Lluís Arcos, Ramón López de Mántaras:
TempoExpress, a CBR Approach to Musical Tempo Transformations. ECCBR 2004: 601-615 - [c2]Maarten Grachten, Josep Lluís Arcos, Ramón López de Mántaras:
Melodic Similarity: Looking for a Good Abstraction Level. ISMIR 2004 - 2003
- [c1]Josep Lluís Arcos
, Maarten Grachten, Ramón López de Mántaras:
Extracting Performers' Behaviors to Annotate Cases in a CBR System for Musical Tempo Transformations. ICCBR 2003: 20-34
Coauthor Index
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