309 citations · 1.2k across the 38 of their papers we have counts for
4 papers · 1 filter
Towards Sparse Hierarchical Graph Classifiers
Cătălina Cangea, Petar Veličković, Nikola Jovanović +2
Recent advances in representation learning on graphs, mainly leveraging graph convolutional networks, have brought a substantial improvement on many graph-based benchmark tasks. Wh…
Deep Graph Infomax
Petar Veličković, William Fedus, William L. Hamilton +3
We present Deep Graph Infomax (DGI), a general approach for learning node representations within graph-structured data in an unsupervised manner. DGI relies on maximizing mutual in…
Attentive cross-modal paratope prediction
Andreea Deac, Petar Veličković, Pietro Sormanni
Antibodies are a critical part of the immune system, having the function of directly neutralising or tagging undesirable objects (the antigens) for future destruction. Being able t…
Automatic Inference of Cross-modal Connection Topologies for X-CNNs
Laurynas Karazija, Petar Veličković, Pietro Liò
This paper introduces a way to learn cross-modal convolutional neural network (X-CNN) architectures from a base convolutional network (CNN) and the training data to reduce the desi…