70 citations · 70 across the 1 of their papers we have counts for
4 papers
Rethinking Graph Transformers with Spectral Attention
Devin Kreuzer, Dominique Beaini, William L. Hamilton +2
In recent years, the Transformer architecture has proven to be very successful in sequence processing, but its application to other data structures, such as graphs, has remained li…
Geodesics in fibered latent spaces: A geometric approach to learning correspondences between conditions
Tariq Daouda, Reda Chhaibi, Prudencio Tossou +1
This work introduces a geometric framework and a novel network architecture for creating correspondences between samples of different conditions. Under this formalism, the latent s…
Adaptive Deep Kernel Learning
Prudencio Tossou, Basile Dura, Francois Laviolette +2
Deep kernel learning provides an elegant and principled framework for combining the structural properties of deep learning algorithms with the flexibility of kernel methods. By mea…
Towards Interpretable Sparse Graph Representation Learning with Laplacian Pooling
Emmanuel Noutahi, Dominique Beaini, Julien Horwood +2
Recent work in graph neural networks (GNNs) has led to improvements in molecular activity and property prediction tasks. Unfortunately, GNNs often fail to capture the relative impo…