3 papers
cs.LG2020
Adaptive Propagation Graph Convolutional Network
Indro Spinelli, Simone Scardapane, Aurelio Uncini
Graph convolutional networks (GCNs) are a family of neural network models that perform inference on graph data by interleaving vertex-wise operations and message-passing exchanges…
stat.ML2019
Efficient data augmentation using graph imputation neural networks
Indro Spinelli, Simone Scardapane, Michele Scarpiniti +1
Recently, data augmentation in the semi-supervised regime, where unlabeled data vastly outnumbers labeled data, has received a considerable attention. In this paper, we describe an…
cs.LG2019
Missing Data Imputation with Adversarially-trained Graph Convolutional Networks
Indro Spinelli, Simone Scardapane, Aurelio Uncini
Missing data imputation (MDI) is a fundamental problem in many scientific disciplines. Popular methods for MDI use global statistics computed from the entire data set (e.g., the fe…