112 citations · 389 across the 35 of their papers we have counts for
4 papers · 2 filters
ChebLieNet: Invariant Spectral Graph NNs Turned Equivariant by Riemannian Geometry on Lie Groups
Hugo Aguettaz, Erik J. Bekkers, Michaël Defferrard
We introduce ChebLieNet, a group-equivariant method on (anisotropic) manifolds. Surfing on the success of graph- and group-based neural networks, we take advantage of the recent de…
Interpretable ECG classification via a query-based latent space traversal (qLST)
Melle B. Vessies, Sharvaree P. Vadgama, Rutger R. van de Leur +4
Electrocardiography (ECG) is an effective and non-invasive diagnostic tool that measures the electrical activity of the heart. Interpretation of ECG signals to detect various abnor…
Geometric and Physical Quantities Improve E(3) Equivariant Message Passing
Johannes Brandstetter, Rob Hesselink, Elise van der Pol +2
Including covariant information, such as position, force, velocity or spin is important in many tasks in computational physics and chemistry. We introduce Steerable E(3) Equivarian…
CKConv: Continuous Kernel Convolution For Sequential Data
David W. Romero, Anna Kuzina, Erik J. Bekkers +2
Conventional neural architectures for sequential data present important limitations. Recurrent networks suffer from exploding and vanishing gradients, small effective memory horizo…