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08/07/2023
On genuine invariance learning without weight-tying
In this paper, we investigate properties and limitations of invariance l...
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06/24/2023
Regular SE(3) Group Convolutions for Volumetric Medical Image Analysis
Regular group convolutional neural networks (G-CNNs) have been shown to ...
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05/03/2023
An Exploration of Conditioning Methods in Graph Neural Networks
The flexibility and effectiveness of message passing based graph neural ...
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01/25/2023
Modelling Long Range Dependencies in N-D: From Task-Specific to a General Purpose CNN
Performant Convolutional Neural Network (CNN) architectures must be tail...
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06/07/2022
Towards a General Purpose CNN for Long Range Dependencies in ND
The use of Convolutional Neural Networks (CNNs) is widespread in Deep Le...
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11/23/2021
ChebLieNet: Invariant Spectral Graph NNs Turned Equivariant by Riemannian Geometry on Lie Groups
We introduce ChebLieNet, a group-equivariant method on (anisotropic) man...
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11/14/2021
Towards Lightweight Controllable Audio Synthesis with Conditional Implicit Neural Representations
The high temporal resolution of audio and our perceptual sensitivity to ...
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10/25/2021
Exploiting Redundancy: Separable Group Convolutional Networks on Lie Groups
Group convolutional neural networks (G-CNNs) have been shown to increase...
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10/15/2021
FlexConv: Continuous Kernel Convolutions with Differentiable Kernel Sizes
When designing Convolutional Neural Networks (CNNs), one must select the...
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02/04/2021
CKConv: Continuous Kernel Convolution For Sequential Data
Conventional neural architectures for sequential data present important ...
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06/09/2020
Wavelet Networks: Scale Equivariant Learning From Raw Waveforms
Inducing symmetry equivariance in deep neural architectures has resolved...
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02/20/2020
Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image Analysis
Rotation-invariance is a desired property of machine-learning models for...
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02/07/2020
Attentive Group Equivariant Convolutional Networks
Although group convolutional networks are able to learn powerful represe...
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09/26/2019
B-Spline CNNs on Lie Groups
Group convolutional neural networks (G-CNNs) can be used to improve clas...
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04/10/2018
Roto-Translation Covariant Convolutional Networks for Medical Image Analysis
We propose a framework for rotation and translation covariant deep learn...
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03/10/2016
