Time series synthesis is an important research topic in the field of dee...
Score-based generative models (SGMs) are a recently proposed paradigm fo...
The problem of processing very long time-series data (e.g., a length of ...
Deep learning inspired by differential equations is a recent research tr...
Tabular data synthesis has received wide attention in the literature. Th...
There were fierce debates on whether the non-linear embedding propagatio...
Mobile digital billboards are an effective way to augment brand-awarenes...
Collaborative filtering (CF) is a long-standing problem of recommender
s...
We present a prediction-driven optimization framework to maximize the ma...
Synthesizing tabular data is attracting much attention these days for va...
Neural ordinary differential equations (NODEs) presented a new paradigm ...