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Found 5 papers, 2 papers with code
Probabilistic Future Prediction for Video Scene Understanding
We present a novel deep learning architecture for probabilistic future prediction from video.
A Learnable ScatterNet: Locally Invariant Convolutional Layers
We do this by breaking down the scattering orders into single convolutional-like layers we call 'locally invariant' layers, and adding a learned mixing term to this layer.
A Framework for Implementing Machine Learning on Omics Data
The potential benefits of applying machine learning methods to -omics data are becoming increasingly apparent, especially in clinical settings.
Deep Learning in the Wavelet Domain
We are stimulated by both Mallat's scattering transform and the idea of filtering in the Fourier domain.
Visualizing and Improving Scattering Networks
These complex patterns may be useful for texture classification, but are quite dissimilar from the patterns visualized in second and third layers of Convolutional Neural Networks (CNNs) - the current state of the art Image Classifiers.
