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Artificial neural networks (ANNs) are a broad class of computational models loosely based on biological neural networks. They encompass feedforward NNs (including "deep" NNs), convolutional NNs, recurrent NNs, etc.
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How to modify an NN's loss and/or optimizer for regression where dataset is mostly 0?
Currently, I am using a U-Net with skips to predict images. These images are based on data from 30 minutes prior. Most of the true image is filled with 0, with a range of approximately [0,50]. The net …
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Spatial Verification Techniques for Image Prediction
I am working on an image prediction problem, where we use a U-Net to predict a real-valued image. I've found that conventional metrics like MSE, r^2, MAE, etc just don't really cut it. What are some o …