Application of Deep Convolutional Neural Networks for Detecting Extreme Weather in Climate Datasets
A Kronecker-factored approximate Fisher matrix for convolution layers
Hierarchical Recurrent Neural Networks for Long-Term Dependencies
Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction
Modern artificial intelligence ( AI ) techniques can aid forecasters on a wide variety of high-impact weather phenomena . USING ARTIFICIAL INTELLIGENCE TO IMPROVE REAL-TIME DECISION-MAKING FOR HIGH-IMPACT WEATHER
Deep Belief Networks Are Compact Universal Approximators