Publications

Towards a General Purpose CNN for Long Range Dependencies in $N$D

David W. Romero, David M. Knigge, Albert Gu, Erik J. Bekkers, Efstratios Gavves, Jakub M. Tomczak, Mark Hoogendoorn

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Learning Equivariances and Partial Equivariances From Data

David W. Romero, Suhas Lohit

FlexConv: Continuous Kernel Convolutions With Differentiable Kernel Sizes

David W. Romero, Robert-Jan Bruintjes, Jakub M. Tomczak, Erik J. Bekkers, Mark Hoogendoorn, Jan van Gemert

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CKConv: Continuous Kernel Convolution For Sequential Data

David W. Romero, Anna Kuzina, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn

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Group Equivariant Stand-Alone Self-Attention For Vision

David W. Romero, Jean-Baptiste Cordonnier

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Wavelet Networks: Scale Equivariant Learning From Raw Waveforms

David W. Romero, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn

Attentive Group Equivariant Convolutional Networks

David W. Romero, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn

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Co-Attentive Equivariant Neural Networks: Focusing Equivariance On Transformations Co-Occurring in Data

David W. Romero, Mark Hoogendoorn

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