David W. Romero
David W. Romero
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Conference paper
Preprint
Date
2022
2021
2020
2019
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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Slides
Learning Partial Equivariances From Data
David W. Romero
,
Suhas Lohit
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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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Poster
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Demos
CKConv: Continuous Kernel Convolution For Sequential Data
David W. Romero
,
Anna Kuzina
,
Erik J. Bekkers
,
Jakub M. Tomczak
,
Mark Hoogendoorn
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Demos
Group Equivariant Stand-Alone Self-Attention For Vision
David W. Romero
,
Jean-Baptiste Cordonnier
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Slides
Demos
Wavelet Networks: Scale Equivariant Learning From Raw Waveforms
David W. Romero
,
Erik J. Bekkers
,
Jakub M. Tomczak
,
Mark Hoogendoorn
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Code
Attentive Group Equivariant Convolutional Networks
David W. Romero
,
Erik J. Bekkers
,
Jakub M. Tomczak
,
Mark Hoogendoorn
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Code
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Video
Co-Attentive Equivariant Neural Networks: Focusing Equivariance On Transformations Co-Occurring in Data
David W. Romero
,
Mark Hoogendoorn
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