21 citations · 22 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 1 cited
Operator-learning-inspired Modeling of Neural Ordinary Differential Equations
Woojin Cho, Seunghyeon Cho, Hyundong Jin +6
Neural ordinary differential equations (NODEs), one of the most influential works of the differential equation-based deep learning, are to continuously generalize residual networks…
cs.LG2022★ 21 cited
GT-GAN: General Purpose Time Series Synthesis with Generative Adversarial Networks
Jinsung Jeon, Jeonghak Kim, Haryong Song +2
Time series synthesis is an important research topic in the field of deep learning, which can be used for data augmentation. Time series data types can be broadly classified into r…