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ORCIDCyrus Vahidi
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2020 – today
- 2023
[c2]Cyrus Vahidi, Shubhr Singh, Emmanouil Benetos, Huy Phan, Dan Stowell
, György Fazekas, Mathieu Lagrange:
Perceptual Musical Similarity Metric Learning with Graph Neural Networks. WASPAA 2023: 1-5- [i5]Cyrus Vahidi, Han Han, Changhong Wang, Mathieu Lagrange, György Fazekas, Vincent Lostanlen:
Mesostructures: Beyond Spectrogram Loss in Differentiable Time-Frequency Analysis. CoRR abs/2301.10183 (2023) - [i4]Giovanni Bindi, Nils Demerlé, Rodrigo Diaz, David Genova, Aliénor Golvet, Ben Hayes, Jiawen Huang, Lele Liu, Vincent Martos, Sarah Nabi, Teresa Pelinski, Lenny Renault, Saurjya Sarkar, Pedro Sarmento, Cyrus Vahidi, Lewis Wolstanholme, Yixiao Zhang, Axel Roebel, Nick Bryan-Kinns, Jean-Louis Giavitto, Mathieu Barthet:
AI (r)evolution - where are we heading? Thoughts about the future of music and sound technologies in the era of deep learning. CoRR abs/2310.18320 (2023) - 2022
- [i3]John Muradeli, Cyrus Vahidi, Changhong Wang, Han Han, Vincent Lostanlen, Mathieu Lagrange, George Fazekas:
Differentiable Time-Frequency Scattering in Kymatio. CoRR abs/2204.08269 (2022) - 2021
- [c1]Cyrus Vahidi, Charalampos Saitis, György Fazekas:
A Modulation Front-End for Music Audio Tagging. IJCNN 2021: 1-7 - [i2]Cyrus Vahidi, Charalampos Saitis, György Fazekas:
A Modulation Front-End for Music Audio Tagging. CoRR abs/2105.11836 (2021) - 2020
- [i1]Cyrus Vahidi, George Fazekas, Charalampos Saitis, Alessandro Palladini:
Timbre Space Representation of a Subtractive Synthesizer. CoRR abs/2009.11706 (2020)
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