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David W. Romero
David W. Romero
PhD Student, Vrije Universiteit Amsterdam
Verified email at vu.nl - Homepage
Title
Cited by
Cited by
Year
CKConv: Continuous Kernel Convolution For Sequential Data
DW Romero, A Kuzina, EJ Bekkers, JM Tomczak, M Hoogendoorn
International Conference on Learning Representations (ICLR), 2022, 2021
792021
Attentive Group Equivariant Convolutional Networks
DW Romero, EJ Bekkers, JM Tomczak, M Hoogendoorn
International Conference on Machine Learning (ICML), 2020, 2020
692020
Flexconv: Continuous kernel convolutions with differentiable kernel sizes
DW Romero, RJ Bruintjes, JM Tomczak, EJ Bekkers, M Hoogendoorn, ...
International Conference on Learning Representations (ICLR), 2022, 2021
612021
Group Equivariant Stand-Alone Self-Attention For Vision
DW Romero, JB Cordonnier
International Conference on Learning Representations (ICLR), 2021, 2020
492020
Learning Equivariances and Partial Equivariances from Data
DW Romero, S Lohit
Advances in Neural Information Processing Systems 35 (NeurIPS 2022), 2021
25*2021
Co-Attentive Equivariant Neural Networks: Focusing Equivariance On Transformations Co-Occurring In Data
DW Romero, M Hoogendoorn
International Conference on Learning Representations (ICLR), 2020, 2019
242019
Exploiting Redundancy: Separable Group Convolutional Networks on Lie Groups
DM Knigge, DW Romero, EJ Bekkers
International Conference on Machine Learning (ICML), 2022, 2021
172021
Relaxing Equivariance Constraints with Non-stationary Continuous Filters
TFA van der Ouderaa, DW Romero, M van der Wilk
Advances in Neural Information Processing Systems 36 (NeurIPS 2022), 2022
162022
Wavelet networks: Scale equivariant learning from raw waveforms
DW Romero, EJ Bekkers, JM Tomczak, M Hoogendoorn
arXiv preprint arXiv:2006.05259, 2020
142020
Towards a general purpose CNN for long range dependencies in ND
DW Romero, DM Knigge, A Gu, EJ Bekkers, E Gavves, JM Tomczak, ...
Workshop on Continuous Time Methods for Machine Learning (ICML 2022), 2022
82022
Modelling Long Range Dependencies in ND: From Task-Specific to a General Purpose CNN
DM Knigge, DW Romero, A Gu, E Gavves, EJ Bekkers, JM Tomczak, ...
International Conference on Learning Representations (ICLR), 2023, 2023
52023
DNArch: Learning Convolutional Neural Architectures by Backpropagation
DW Romero, N Zeghidour
arXiv preprint arXiv:2302.05400, 2023
12023
Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions
S Massaroli, M Poli, DY Fu, H Kumbong, RN Parnichkun, A Timalsina, ...
arXiv preprint arXiv:2310.18780, 2023
2023
Fast, Expressive SE Equivariant Networks through Weight-Sharing in Position-Orientation Space
EJ Bekkers, S Vadgama, RD Hesselink, PA van der Linden, DW Romero
arXiv preprint arXiv:2310.02970, 2023
2023
Learned Gridification for Efficient Point Cloud Processing
PA Van der Linden, DW Romero, EJ Bekkers
arXiv preprint arXiv:2307.14354, 2023
2023
Generative Fourier-Based Auto-encoders: Preliminary Results
A Zonta, A El Hassouni, DW Romero, JM Tomczak
Machine Learning, Optimization, and Data Science: 6th International …, 2020
2020
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