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Found 8 papers, 1 papers with code
PAUNet: Precipitation Attention-based U-Net for rain prediction from satellite radiance data
This paper introduces Precipitation Attention-based U-Net (PAUNet), a deep learning architecture for predicting precipitation from satellite radiance data, addressing the challenges of the Weather4cast 2023 competition.
SSG2: A new modelling paradigm for semantic segmentation
By adding this "temporal" dimension, we exploit strong signal correlations between successive observations in the sequence to reduce error rates.
Earth Virtualization Engines -- A Technical Perspective
Participants of the Berlin Summit on Earth Virtualization Engines (EVEs) discussed ideas and concepts to improve our ability to cope with climate change.
Machine Learning based Parameter Sensitivity of Regional Climate Models -- A Case Study of the WRF Model for Heat Extremes over Southeast Australia
However, parameter sensitivity analysis (SA) of regional models for heat extremes is largely unexplored.
Movement Analytics: Current Status, Application to Manufacturing, and Future Prospects from an AI Perspective
From an application perspective, we review applications of these methods to movement analytics in a general sense and across various industries.
Optimizing the optimizer for data driven deep neural networks and physics informed neural networks
We investigate the role of the optimizer in determining the quality of the model fit for neural networks with a small to medium number of parameters.
A Deep Learning Model for Forecasting Global Monthly Mean Sea Surface Temperature Anomalies
However, the prediction of the marine heatwaves in the southeast Indian Ocean, the Ningaloo Ni\~{n}o, shows limited skill.
Exploiting the Power of Levenberg-Marquardt Optimizer with Anomaly Detection in Time Series
Literature reviews have shown that the LM can be very powerful and effective on moderate function approximation problems when the number of weights in the network is not more than a couple of hundred.
