| 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 | 57 | 2017 |
| 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 | 29 | 2021 |
| 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 | 25 | 2019 |
| 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 | 22 | 2021 |
| The greek music dataset D Makris, I Karydis, S Sioutas Proceedings of the 16th International Conference on Engineering Applications …, 2015 | 17 | 2015 |
| The greek audio dataset D Makris, KL Kermanidis, I Karydis Artificial Intelligence Applications and Innovations: AIAI 2014 Workshops …, 2014 | 16 | 2014 |
| 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 | 14 | 2016 |
| 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 | 13 | 2016 |
| Probabilistic Modular Bass Voice Leading in Melodic Harmonisation. D Makris, MA Kaliakatsos-Papakostas, E Cambouropoulos ISMIR, 323-329, 2015 | 12 | 2015 |
| 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 | 11 | 2013 |
| 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 | 10 | 2022 |
| Deepdrum: An adaptive conditional neural network D Makris, M Kaliakatsos-Papakostas, KL Kermanidis arXiv preprint arXiv:1809.06127, 2018 | 10 | 2018 |
| VISA3: Refining the voice integration/segregation algorithm D Makris, I Karydis, E Cambouropoulos Sound and Music Computing Conference (SMC 2016), 2016 | 8 | 2016 |
| 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 | 7 | 2022 |
| 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 | 6 | 2016 |
| 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 | 5 | 2015 |
| 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 | | |
Maximos Kaliakatsos-PapakostasHellenic Mediterranean UniversityVerified email at hmu.gr
