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The Edge of Orthogonality: A Simple View of What Makes BYOL Tick

The Edge of Orthogonality: A Simple View of What Makes BYOL Tick

9 February 2023
Pierre Harvey Richemond
Allison C. Tam
Yunhao Tang
Florian Strub
Bilal Piot
Felix Hill
    SSL
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Papers citing "The Edge of Orthogonality: A Simple View of What Makes BYOL Tick"

16 / 16 papers shown
Title
FreCT: Frequency-augmented Convolutional Transformer for Robust Time Series Anomaly Detection
FreCT: Frequency-augmented Convolutional Transformer for Robust Time Series Anomaly Detection
Wenxin Zhang
Ding Xu
Guangzhen Yao
Xiaojian Lin
Renxiang Guan
Chengze Du
Renda Han
Xi Xuan
Cuicui Luo
AI4TS
42
0
0
02 May 2025
Representation Learning via Non-Contrastive Mutual Information
Representation Learning via Non-Contrastive Mutual Information
Z. Guo
Bernardo Avila-Pires
Khimya Khetarpal
Dale Schuurmans
Bo Dai
SSL
61
0
0
23 Apr 2025
The Hidden Pitfalls of the Cosine Similarity Loss
The Hidden Pitfalls of the Cosine Similarity Loss
Andrew Draganov
Sharvaree P. Vadgama
Erik J. Bekkers
SSL
19
0
0
24 Jun 2024
On the Effectiveness of Supervision in Asymmetric Non-Contrastive
  Learning
On the Effectiveness of Supervision in Asymmetric Non-Contrastive Learning
Jeongheon Oh
Kibok Lee
SSL
30
1
0
16 Jun 2024
$V_kD:$ Improving Knowledge Distillation using Orthogonal Projections
VkD:V_kD:Vk​D: Improving Knowledge Distillation using Orthogonal Projections
Roy Miles
Ismail Elezi
Jiankang Deng
34
9
0
10 Mar 2024
DiffClone: Enhanced Behaviour Cloning in Robotics with Diffusion-Driven
  Policy Learning
DiffClone: Enhanced Behaviour Cloning in Robotics with Diffusion-Driven Policy Learning
Sabariswaran Mani
Sreyas Venkataraman
Abhranil Chandra
Adyan Rizvi
Yash Sirvi
Soumojit Bhattacharya
Aritra Hazra
OffRL
13
1
0
17 Jan 2024
Graph-level Representation Learning with Joint-Embedding Predictive Architectures
Graph-level Representation Learning with Joint-Embedding Predictive Architectures
Geri Skenderi
Hang Li
Jiliang Tang
Marco Cristani
AI4TS
GNN
44
3
0
27 Sep 2023
How to Scale Your EMA
How to Scale Your EMA
Dan Busbridge
Jason Ramapuram
Pierre Ablin
Tatiana Likhomanenko
Eeshan Gunesh Dhekane
Xavier Suau
Russ Webb
17
17
0
25 Jul 2023
Towards a Unified Theoretical Understanding of Non-contrastive Learning
  via Rank Differential Mechanism
Towards a Unified Theoretical Understanding of Non-contrastive Learning via Rank Differential Mechanism
Zhijian Zhuo
Yifei Wang
Jinwen Ma
Yisen Wang
38
24
0
04 Mar 2023
Implicit variance regularization in non-contrastive SSL
Implicit variance regularization in non-contrastive SSL
Manu Srinath Halvagal
Axel Laborieux
Friedemann Zenke
29
8
0
09 Dec 2022
Neural Eigenfunctions Are Structured Representation Learners
Neural Eigenfunctions Are Structured Representation Learners
Zhijie Deng
Jiaxin Shi
Hao Zhang
Peng Cui
Cewu Lu
Jun Zhu
39
14
0
23 Oct 2022
Fast and accurate optimization on the orthogonal manifold without
  retraction
Fast and accurate optimization on the orthogonal manifold without retraction
Pierre Ablin
Gabriel Peyré
40
26
0
15 Feb 2021
Understanding self-supervised Learning Dynamics without Contrastive
  Pairs
Understanding self-supervised Learning Dynamics without Contrastive Pairs
Yuandong Tian
Xinlei Chen
Surya Ganguli
SSL
132
278
0
12 Feb 2021
Scaling Up Visual and Vision-Language Representation Learning With Noisy
  Text Supervision
Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision
Chao Jia
Yinfei Yang
Ye Xia
Yi-Ting Chen
Zarana Parekh
Hieu H. Pham
Quoc V. Le
Yun-hsuan Sung
Zhen Li
Tom Duerig
VLM
CLIP
293
3,683
0
11 Feb 2021
BYOL works even without batch statistics
BYOL works even without batch statistics
Pierre Harvey Richemond
Jean-Bastien Grill
Florent Altché
Corentin Tallec
Florian Strub
...
Samuel L. Smith
Soham De
Razvan Pascanu
Bilal Piot
Michal Valko
SSL
242
114
0
20 Oct 2020
Spectral Inference Networks: Unifying Deep and Spectral Learning
Spectral Inference Networks: Unifying Deep and Spectral Learning
David Pfau
Stig Petersen
Ashish Agarwal
David Barrett
Kimberly L. Stachenfeld
49
40
0
06 Jun 2018
1