17 citations · 22 across the 4 of their papers we have counts for
5 papers
Neural Priority Queues for Graph Neural Networks
Rishabh Jain, Petar Veličković, Pietro Liò
Graph Neural Networks (GNNs) have shown considerable success in neural algorithmic reasoning. Many traditional algorithms make use of an explicit memory in the form of a data struc…
Learning Graph Search Heuristics
Michal Pándy, Weikang Qiu, Gabriele Corso +4
Searching for a path between two nodes in a graph is one of the most well-studied and fundamental problems in computer science. In numerous domains such as robotics, AI, or biology…
Continuous Neural Algorithmic Planners
Yu He, Petar Veličković, Pietro Liò +1
Neural algorithmic reasoning studies the problem of learning algorithms with neural networks, especially with graph architectures. A recent proposal, XLVIN, reaps the benefits of u…
Neural Distance Embeddings for Biological Sequences
Gabriele Corso, Rex Ying, Michal Pándy +3
The development of data-dependent heuristics and representations for biological sequences that reflect their evolutionary distance is critical for large-scale biological research.…
Neural message passing for joint paratope-epitope prediction
Alice Del Vecchio, Andreea Deac, Pietro Liò +1
Antibodies are proteins in the immune system which bind to antigens to detect and neutralise them. The binding sites in an antibody-antigen interaction are known as the paratope an…