358 citations · 360 across the 2 of their papers we have counts for
3 papers
cs.SD2022★ 2 cited
Conditional variational autoencoder to improve neural audio synthesis for polyphonic music sound
Seokjin Lee, Minhan Kim, Seunghyeon Shin +3
Deep generative models for audio synthesis have recently been significantly improved. However, the task of modeling raw-waveforms remains a difficult problem, especially for audio…
cs.LG2021
Deep Neural Networks and End-to-End Learning for Audio Compression
Daniela N. Rim, Inseon Jang, Heeyoul Choi
Recent achievements in end-to-end deep learning have encouraged the exploration of tasks dealing with highly structured data with unified deep network models. Having such models fo…
cs.LG2018★ 358 cited
Deep learning for determining a near-optimal topological design without any iteration
Yonggyun Yu, Taeil Hur, Jaeho Jung +1
In this study, we propose a novel deep learning-based method to predict an optimized structure for a given boundary condition and optimization setting without using any iterative s…