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Dimos Makris
Dimos Makris
Machine Learning Researcher at Music Tribe, Sweden
Email confirmado em musictribe.com
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Combining LSTM and feed forward neural networks for conditional rhythm composition
D Makris, M Kaliakatsos-Papakostas, I Karydis, KL Kermanidis
Engineering Applications of Neural Networks: 18th International Conference …, 2017
572017
Generating lead sheets with affect: A novel conditional seq2seq framework
D Makris, KR Agres, D Herremans
2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021
302021
Conditional neural sequence learners for generating drums’ rhythms
D Makris, M Kaliakatsos-Papakostas, I Karydis, KL Kermanidis
Neural Computing and Applications 31 (6), 1793-1804, 2019
252019
Hierarchical recurrent neural networks for conditional melody generation with long-term structure
G Zixun, D Makris, D Herremans
2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021
242021
The greek music dataset
D Makris, I Karydis, S Sioutas
Proceedings of the 16th International Conference on Engineering Applications …, 2015
172015
The greek audio dataset
D Makris, KL Kermanidis, I Karydis
Artificial Intelligence Applications and Innovations: AIAI 2014 Workshops …, 2014
162014
Learning and creating novel harmonies in diverse musical idioms: An adaptive modular melodic harmonisation system
M Kaliakatsos-Papakostas, D Makris, C Tsougras, E Cambouropoulos
Journal of Creative Music Systems 1 (1), 2016
142016
Automatic melodic harmonization: An overview, challenges and future directions
D Makris, I Kayrdis, S Sioutas
Trends in music information seeking, behavior, and retrieval for creativity …, 2016
132016
Predicting emotion from music videos: exploring the relative contribution of visual and auditory information to affective responses
P Chua, D Makris, D Herremans, G Roig, K Agres
arXiv preprint arXiv:2202.10453, 2022
122022
Probabilistic Modular Bass Voice Leading in Melodic Harmonisation.
D Makris, MA Kaliakatsos-Papakostas, E Cambouropoulos
ISMIR, 323-329, 2015
122015
Could you help me to change the variables? Comparing instruction to encouragement for teaching programming
D Makris, K Euaggelopoulos, K Chorianopoulos, MN Giannakos
Proceedings of the 8th Workshop in Primary and Secondary Computing Education …, 2013
112013
Deepdrum: An adaptive conditional neural network
D Makris, M Kaliakatsos-Papakostas, KL Kermanidis
arXiv preprint arXiv:1809.06127, 2018
102018
Conditional drums generation using compound word representations
D Makris, G Zixun, M Kaliakatsos-Papakostas, D Herremans
International Conference on Computational Intelligence in Music, Sound, Art …, 2022
82022
VISA3: Refining the voice integration/segregation algorithm
D Makris, I Karydis, E Cambouropoulos
Sound and Music Computing Conference (SMC 2016), 2016
82016
Learning and blending harmonies in the context of a melodic harmonisation assistant
M Kaliakatsos-Papakostas, D Makris, A Zacharakis, C Tsougras, ...
Artificial Intelligence Applications and Innovations: 12th IFIP WG 12.5 …, 2016
62016
A probabilistic approach to determining bass voice leading in melodic harmonisation
D Makris, M Kaliakatsos-Papakostas, E Cambouropoulos
International Conference on Mathematics and Computation in Music, 128-134, 2015
52015
Hierarchical Recurrent Neural Networks for Conditional Melody Generation with Long-term Structure
Z Guo, M Dimos, H Dorien
arXiv preprint arXiv:2102.09794, 2021
2021
VISA3
D Makris, I Karydis, E Cambouropoulos
Proceedings of the Sound and Music Computing Conference 2016, 2016
2016
Learning and blending harmonies in a melodic harmonisation assistant
M Kaliakatsos-Papakostas, D Makris, A Zacharakis, C Tsougras, ...
Automatic Melodic Harmonization
D Makris, I Karydis, S Sioutas
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