Search Results for author:
Found 5 papers, 3 papers with code
Four-hour thunderstorm nowcasting using deep diffusion models of satellite
In terms of application, our system operates efficiently (forecasting 4 hours of convection in 8 minutes), and is highly transferable with the potential to collaborate with multiple satellites for global convection nowcasting.
TinyPredNet: A Lightweight Framework for Satellite Image Sequence Prediction
In this article, we propose a lightweight prediction framework TinyPredNet for satellite image sequence prediction, in which a spatial encoder and decoder model the intra-frame appearance features and a temporal translator captures inter-frame motion patterns.
DiffCast: A Unified Framework via Residual Diffusion for Precipitation Nowcasting
A unified and flexible framework that can equip any type of spatio-temporal models is proposed based on residual diffusion, which effectively tackles the shortcomings of previous methods.
MSTCGAN: Multiscale time conditional generative adversarial network for long-term satellite image sequence prediction
To address the sequential error accumulation issue, MSTCGAN adopts a parallel prediction framework to produce the future image sequences by a one-hot time condition input.
Enhancing Cross-target Stance Detection with Transferable Semantic-Emotion Knowledge
Specifically, a semantic-emotion heterogeneous graph is constructed from external semantic and emotion lexicons, which is then fed into a graph convolutional network to learn multi-hop semantic connections between words and emotion tags.
