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Run Away From your Teacher: Understanding BYOL by a Novel
  Self-Supervised Approach

Run Away From your Teacher: Understanding BYOL by a Novel Self-Supervised Approach

22 November 2020
Haizhou Shi
Dongliang Luo
Siliang Tang
Jian Wang
Yueting Zhuang
    SSL
ArXivPDFHTML

Papers citing "Run Away From your Teacher: Understanding BYOL by a Novel Self-Supervised Approach"

6 / 6 papers shown
Title
A Unified Approach to Domain Incremental Learning with Memory: Theory
  and Algorithm
A Unified Approach to Domain Incremental Learning with Memory: Theory and Algorithm
Haizhou Shi
Hao Wang
CLL
32
18
0
18 Oct 2023
SGL-PT: A Strong Graph Learner with Graph Prompt Tuning
SGL-PT: A Strong Graph Learner with Graph Prompt Tuning
Yun Zhu
Jianhao Guo
Siliang Tang
17
28
0
24 Feb 2023
Self-Labeling Refinement for Robust Representation Learning with
  Bootstrap Your Own Latent
Self-Labeling Refinement for Robust Representation Learning with Bootstrap Your Own Latent
Siddhant Garg
Dhruval Jain
SSL
36
0
0
09 Apr 2022
Improved Baselines with Momentum Contrastive Learning
Improved Baselines with Momentum Contrastive Learning
Xinlei Chen
Haoqi Fan
Ross B. Girshick
Kaiming He
SSL
267
3,369
0
09 Mar 2020
There Are Many Consistent Explanations of Unlabeled Data: Why You Should
  Average
There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average
Ben Athiwaratkun
Marc Finzi
Pavel Izmailov
A. Wilson
199
243
0
14 Jun 2018
Mean teachers are better role models: Weight-averaged consistency
  targets improve semi-supervised deep learning results
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
Antti Tarvainen
Harri Valpola
OOD
MoMe
261
1,275
0
06 Mar 2017
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