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Found 7 papers, 5 papers with code
DeeplyTough: Learning Structural Comparison of Protein Binding Sites
Protein binding site comparison (pocket matching) is of importance in drug discovery.
Deep Learning on Attributed Graphs: A Journey from Graphs to Their Embeddings and Back
A graph is a powerful concept for representation of relations between pairs of entities.
GraphVAE: Towards Generation of Small Graphs Using Variational Autoencoders
Deep learning on graphs has become a popular research topic with many applications.
Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs
We propose a novel deep learning-based framework to tackle the challenge of semantic segmentation of large-scale point clouds of millions of points.
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Semantic Segmentation
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Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs
A number of problems can be formulated as prediction on graph-structured data.
A Deep Metric for Multimodal Registration
Multimodal registration is a challenging problem in medical imaging due the high variability of tissue appearance under different imaging modalities.
OnionNet: Sharing Features in Cascaded Deep Classifiers
The focus of our work is speeding up evaluation of deep neural networks in retrieval scenarios, where conventional architectures may spend too much time on negative examples.
