Understanding and Testing Generalization of Deep Networks on
Out-of-Distribution Data

Understanding and Testing Generalization of Deep Networks on Out-of-Distribution Data

17 November 2021

Rui Hu

Rui Hu

Papers citing "Understanding and Testing Generalization of Deep Networks on Out-of-Distribution Data"

6 / 6 papers shown

Title
Holistic chemical evaluation reveals pitfalls in reaction prediction models Victor Sabanza Gil Andres M Bran Malte Franke Remi Schlama J. Luterbacher Philippe Schwaller ELM 21 1 0 14 Dec 2023
LaF: Labeling-Free Model Selection for Automated Deep Neural Network Reusing Qiang Hu Yuejun Guo Maxime Cordy Xiaofei Xie Mike Papadakis Yves Le Traon 21 5 0 08 Apr 2022
A benchmark with decomposed distribution shifts for 360 monocular depth estimation G. Albanis N. Zioulis Petros Drakoulis Federico Álvarez D. Zarpalas P. Daras MDE 22 0 0 01 Dec 2021
Deep Domain-Adversarial Image Generation for Domain Generalisation Kaiyang Zhou Yongxin Yang Timothy M. Hospedales Tao Xiang OOD 204 402 0 12 Mar 2020
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 948 20,471 0 17 Apr 2017
Aggregated Residual Transformations for Deep Neural Networks Saining Xie Ross B. Girshick Piotr Dollár Z. Tu Kaiming He 261 10,196 0 16 Nov 2016