Marinka Žitnik

Cross-type Biomedical Named Entity Recognition with Deep Multi-Task Learning

2018 · arXiv (Cornell University)

Motivation: State-of-the-art biomedical named entity recognition (BioNER) systems often require handcrafted features specific to each entity type, such as genes, chemicals and diseases. Although recent studies explored using neural network models for BioNER to free …

GNNExplainer: Generating Explanations for Graph Neural Networks.

2019 · PubMed

Graph Neural Networks (GNNs) are a powerful tool for machine learning on graphs. GNNs combine node feature information with the graph structure by recursively passing neural messages along edges of the input graph. However, incorporating …

Learning Structural Node Embeddings via Diffusion Wavelets

2018

Nodes residing in different parts of a graph can have similar structural roles within their local network topology. The identification of such roles provides key insight into the organization of networks and can be used …