RankMe: Assessing the downstream performance of pretrained self-supervised representations by their rank

5 October 2022

Papers citing "RankMe: Assessing the downstream performance of pretrained self-supervised representations by their rank"

9 / 59 papers shown

Title
Light-weight probing of unsupervised representations for Reinforcement Learning Wancong Zhang Anthony GX-Chen Vlad Sobal Yann LeCun Nicolas Carion SSL OffRL 41 13 0 25 Aug 2022
Using Representation Expressiveness and Learnability to Evaluate Self-Supervised Learning Methods Yuchen Lu Zhen Liu A. Baratin Romain Laroche Rameswar Panda Alessandro Sordoni SSL 23 0 0 02 Jun 2022
Measuring Self-Supervised Representation Quality for Downstream Classification using Discriminative Features Neha Kalibhat Kanika Narang Hamed Firooz Maziar Sanjabi S. Feizi SSL 38 7 0 03 Mar 2022
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 308 7,443 0 11 Nov 2021
Decoupled Contrastive Learning Chun-Hsiao Yeh Cheng-Yao Hong Yen-Chi Hsu Tyng-Luh Liu Yubei Chen Yann LeCun 183 182 0 13 Oct 2021
Compressive Visual Representations Kuang-Huei Lee Anurag Arnab S. Guadarrama John F. Canny Ian S. Fischer SSL 65 48 0 27 Sep 2021
On Feature Decorrelation in Self-Supervised Learning Tianyu Hua Wenxiao Wang Zihui Xue Sucheng Ren Yue Wang Hang Zhao SSL OOD 133 187 0 02 May 2021
Emerging Properties in Self-Supervised Vision Transformers Mathilde Caron Hugo Touvron Ishan Misra Hervé Jégou Julien Mairal Piotr Bojanowski Armand Joulin 347 5,785 0 29 Apr 2021
Improved Baselines with Momentum Contrastive Learning Xinlei Chen Haoqi Fan Ross B. Girshick Kaiming He SSL 270 3,375 0 09 Mar 2020