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Found 3 papers, 1 papers with code
Operator-learning-inspired Modeling of Neural Ordinary Differential Equations
Neural ordinary differential equations (NODEs), one of the most influential works of the differential equation-based deep learning, are to continuously generalize residual networks and opened a new field.
GT-GAN: General Purpose Time Series Synthesis with Generative Adversarial Networks
Time series synthesis is an important research topic in the field of deep learning, which can be used for data augmentation.
LightMove: A Lightweight Next-POI Recommendation for Taxicab Rooftop Advertising
Among various such mobile billboards, taxicab rooftop devices are emerging in the market as a brand new media.
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