159 citations · 168 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 2 cited
Can Forward Gradient Match Backpropagation?
Louis Fournier, Stéphane Rivaud, Eugene Belilovsky +2
Forward Gradients - the idea of using directional derivatives in forward differentiation mode - have recently been shown to be utilizable for neural network training while avoiding…
cs.LG2022★ 159 cited
Why do tree-based models still outperform deep learning on tabular data?
Léo Grinsztajn, Edouard Oyallon, Gaël Varoquaux
While deep learning has enabled tremendous progress on text and image datasets, its superiority on tabular data is not clear. We contribute extensive benchmarks of standard and nov…
cs.CV2014★ 7 cited
Deep Roto-Translation Scattering for Object Classification
Edouard Oyallon, Stéphane Mallat
Dictionary learning algorithms or supervised deep convolution networks have considerably improved the efficiency of predefined feature representations such as SIFT. We introduce a…