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08/29/2023
Hyperbolic Convolutional Neural Networks
Deep Learning is mostly responsible for the surge of interest in Artific...
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06/18/2021
Steerable Partial Differential Operators for Equivariant Neural Networks
Recent work in equivariant deep learning bears strong similarities to ph...
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06/10/2021
Coordinate Independent Convolutional Networks – Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds
Motivated by the vast success of deep convolutional networks, there is a...
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10/21/2020
A Wigner-Eckart Theorem for Group Equivariant Convolution Kernels
Group equivariant convolutional networks (GCNNs) endow classical convolu...
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03/11/2020
Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs
A common approach to define convolutions on meshes is to interpret them ...
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11/19/2019
General E(2)-Equivariant Steerable CNNs
The big empirical success of group equivariant networks has led in recen...
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06/06/2019
Covariance in Physics and Convolutional Neural Networks
In this proceeding we give an overview of the idea of covariance (or equ...
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02/11/2019
Gauge Equivariant Convolutional Networks and the Icosahedral CNN
The idea of equivariance to symmetry transformations provides one of the...
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11/05/2018
A General Theory of Equivariant CNNs on Homogeneous Spaces
Group equivariant convolutional neural networks (G-CNNs) have recently e...
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07/12/2018
Explorations in Homeomorphic Variational Auto-Encoding
The manifold hypothesis states that many kinds of high-dimensional data ...
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07/06/2018
3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data
We present a convolutional network that is equivariant to rigid body mot...
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03/28/2018
Intertwiners between Induced Representations (with Applications to the Theory of Equivariant Neural Networks)
Group equivariant and steerable convolutional neural networks (regular a...
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11/20/2017