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Speeding up Learning Quantum States through Group Equivariant Convolutional Quantum Ansätze
Han Zheng, Zimu Li, Junyu Liu +2
We develop a theoretical framework for -equivariant convolutional quantum circuits with SU-symmetry, building on and significantly generalizing Jordan's Permutational Qua…
Learning Multiresolution Matrix Factorization and its Wavelet Networks on Graphs
Truong Son Hy, Risi Kondor
Multiresolution Matrix Factorization (MMF) is unusual amongst fast matrix factorization algorithms in that it does not make a low rank assumption. This makes MMF especially well su…
Multiresolution Equivariant Graph Variational Autoencoder
Truong Son Hy, Risi Kondor
In this paper, we propose Multiresolution Equivariant Graph Variational Autoencoders (MGVAE), the first hierarchical generative model to learn and generate graphs in a multiresolut…
Autobahn: Automorphism-based Graph Neural Nets
Erik Henning Thiede, Wenda Zhou, Risi Kondor
We introduce Automorphism-based graph neural networks (Autobahn), a new family of graph neural networks. In an Autobahn, we decompose the graph into a collection of subgraphs and a…