no code implementations • 27 Sep 2023 • Xuanlong Yu, Yi Zuo, Zitao Wang, Xiaowen Zhang, Jiaxuan Zhao, Yuting Yang, Licheng Jiao, Rui Peng, Xinyi Wang, Junpei Zhang, Kexin Zhang, Fang Liu, Roberto Alcover-Couso, Juan C. SanMiguel, Marcos Escudero-Viñolo, Hanlin Tian, Kenta Matsui, Tianhao Wang, Fahmy Adan, Zhitong Gao, Xuming He, Quentin Bouniot, Hossein Moghaddam, Shyam Nandan Rai, Fabio Cermelli, Carlo Masone, Andrea Pilzer, Elisa Ricci, Andrei Bursuc, Arno Solin, Martin Trapp, Rui Li, Angela Yao, Wenlong Chen, Ivor Simpson, Neill D. F. Campbell, Gianni Franchi
This paper outlines the winning solutions employed in addressing the MUAD uncertainty quantification challenge held at ICCV 2023.
no code implementations • 11 Feb 2022 • Rui Guo, Ivor Simpson, Chris Kiefer, Thor Magnusson, Dorien Herremans
We present a novel music generation framework for music infilling, with a user friendly interface.
1 code implementation • 13 Oct 2020 • Rui Guo, Ivor Simpson, Thor Magnusson, Chris Kiefer, Dorien Herremans
Many of the music generation systems based on neural networks are fully autonomous and do not offer control over the generation process.
Sound Symbolic Computation Audio and Speech Processing
2 code implementations • 3 Apr 2018 • Garoe Dorta, Sara Vicente, Lourdes Agapito, Neill D. F. Campbell, Ivor Simpson
This paper demonstrates a novel scheme to incorporate a structured Gaussian likelihood prediction network within the VAE that allows the residual correlations to be modeled.
2 code implementations • CVPR 2018 • Garoe Dorta, Sara Vicente, Lourdes Agapito, Neill D. F. Campbell, Ivor Simpson
This paper is the first work to propose a network to predict a structured uncertainty distribution for a synthesized image.