The Power of Linear Combinations: Learning with Random Convolutions

26 January 2023

Papers citing "The Power of Linear Combinations: Learning with Random Convolutions"

11 / 11 papers shown

Title
How Do Training Methods Influence the Utilization of Vision Models? Paul Gavrikov Shashank Agnihotri M. Keuper J. Keuper 21 2 0 18 Oct 2024
Can Biases in ImageNet Models Explain Generalization? Paul Gavrikov J. Keuper OOD VLM 19 11 0 01 Apr 2024
Understanding the Covariance Structure of Convolutional Filters Asher Trockman Devin Willmott J. Zico Kolter 44 11 0 07 Oct 2022
FreDSNet: Joint Monocular Depth and Semantic Segmentation with Fast Fourier Convolutions Bruno Berenguel-Baeta J. Bermudez-Cameo Jose J. Guerrero MDE 50 15 0 04 Oct 2022
Patches Are All You Need? Asher Trockman J. Zico Kolter ViT 214 395 0 24 Jan 2022
ResNet strikes back: An improved training procedure in timm Ross Wightman Hugo Touvron Hervé Jégou AI4TS 207 477 0 01 Oct 2021
High-Performance Large-Scale Image Recognition Without Normalization Andrew Brock Soham De Samuel L. Smith Karen Simonyan VLM 220 510 0 11 Feb 2021
RepVGG: Making VGG-style ConvNets Great Again Xiaohan Ding X. Zhang Ningning Ma Jungong Han Guiguang Ding Jian-jun Sun 117 1,484 0 11 Jan 2021
Bag of Tricks for Image Classification with Convolutional Neural Networks Tong He Zhi-Li Zhang Hang Zhang Zhongyue Zhang Junyuan Xie Mu Li 216 1,391 0 04 Dec 2018
Aggregated Residual Transformations for Deep Neural Networks Saining Xie Ross B. Girshick Piotr Dollár Z. Tu Kaiming He 261 10,106 0 16 Nov 2016
Xception: Deep Learning with Depthwise Separable Convolutions François Chollet MDE BDL PINN 201 14,190 0 07 Oct 2016