ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2108.07183
  4. Cited By
Improving Self-supervised Learning with Hardness-aware Dynamic
  Curriculum Learning: An Application to Digital Pathology

Improving Self-supervised Learning with Hardness-aware Dynamic Curriculum Learning: An Application to Digital Pathology

16 August 2021
C. Srinidhi
Anne L. Martel
ArXivPDFHTML

Papers citing "Improving Self-supervised Learning with Hardness-aware Dynamic Curriculum Learning: An Application to Digital Pathology"

34 / 34 papers shown
Title
The Evolution of Out-of-Distribution Robustness Throughout Fine-Tuning
The Evolution of Out-of-Distribution Robustness Throughout Fine-Tuning
Anders Andreassen
Yasaman Bahri
Behnam Neyshabur
Rebecca Roelofs
OOD
OODD
61
80
0
30 Jun 2021
When Does Contrastive Visual Representation Learning Work?
When Does Contrastive Visual Representation Learning Work?
Elijah Cole
Xuan S. Yang
Kimberly Wilber
Oisin Mac Aodha
Serge Belongie
SSL
64
124
0
12 May 2021
Self-Supervised Pretraining Improves Self-Supervised Pretraining
Self-Supervised Pretraining Improves Self-Supervised Pretraining
Colorado Reed
Xiangyu Yue
Aniruddha Nrusimha
Sayna Ebrahimi
Vivek Vijaykumar
...
Shanghang Zhang
Devin Guillory
Sean L. Metzger
Kurt Keutzer
Trevor Darrell
52
108
0
23 Mar 2021
Self-supervised driven consistency training for annotation efficient
  histopathology image analysis
Self-supervised driven consistency training for annotation efficient histopathology image analysis
C. Srinidhi
Seung Wook Kim
Fu-Der Chen
Anne L. Martel
SSL
59
110
0
07 Feb 2021
Curriculum Learning: A Survey
Curriculum Learning: A Survey
Petru Soviany
Radu Tudor Ionescu
Paolo Rota
N. Sebe
ODL
107
352
0
25 Jan 2021
Big Self-Supervised Models Advance Medical Image Classification
Big Self-Supervised Models Advance Medical Image Classification
Shekoofeh Azizi
Basil Mustafa
Fiona Ryan
Zach Beaver
Jan Freyberg
...
Alan Karthikesalingam
Simon Kornblith
Ting-Li Chen
Vivek Natarajan
Mohammad Norouzi
SSL
99
513
0
13 Jan 2021
Self-supervised Pre-training with Hard Examples Improves Visual
  Representations
Self-supervised Pre-training with Hard Examples Improves Visual Representations
Chunyuan Li
Xiujun Li
Lei Zhang
Baolin Peng
Mingyuan Zhou
Jianfeng Gao
SSL
64
24
0
25 Dec 2020
When Do Curricula Work?
When Do Curricula Work?
Xiaoxia Wu
Ethan Dyer
Behnam Neyshabur
53
115
0
05 Dec 2020
Overcoming the limitations of patch-based learning to detect cancer in
  whole slide images
Overcoming the limitations of patch-based learning to detect cancer in whole slide images
Ozan Ciga
Tony Xu
S. Nofech-Mozes
S. Noy
F. Lu
Anne L. Martel
42
38
0
01 Dec 2020
Self supervised contrastive learning for digital histopathology
Self supervised contrastive learning for digital histopathology
Ozan Ciga
Tony Xu
Anne L. Martel
SSL
145
311
0
27 Nov 2020
MoCo-CXR: MoCo Pretraining Improves Representation and Transferability
  of Chest X-ray Models
MoCo-CXR: MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models
Hari Sowrirajan
Jingbo Yang
A. Ng
Pranav Rajpurkar
67
86
0
11 Oct 2020
Contrastive Learning with Hard Negative Samples
Contrastive Learning with Hard Negative Samples
Joshua Robinson
Ching-Yao Chuang
S. Sra
Stefanie Jegelka
SSL
115
768
0
09 Oct 2020
Learn like a Pathologist: Curriculum Learning by Annotator Agreement for
  Histopathology Image Classification
Learn like a Pathologist: Curriculum Learning by Annotator Agreement for Histopathology Image Classification
Jerry W. Wei
A. Suriawinata
Bing Ren
Xiaoying Liu
Mikhail Lisovsky
...
Mustafa Nasir-Moin
Naofumi Tomita
Lorenzo Torresani
Jason W. Wei
Saeed Hassanpour
79
49
0
29 Sep 2020
What Should Not Be Contrastive in Contrastive Learning
What Should Not Be Contrastive in Contrastive Learning
Tete Xiao
Xiaolong Wang
Alexei A. Efros
Trevor Darrell
SSL
DRL
64
298
0
13 Aug 2020
Self-Path: Self-supervision for Classification of Pathology Images with
  Limited Annotations
Self-Path: Self-supervision for Classification of Pathology Images with Limited Annotations
Navid Alemi Koohbanani
Balagopal Unnikrishnan
S. Khurram
Pavitra Krishnaswamy
Nasir M. Rajpoot
SSL
62
164
0
12 Aug 2020
Demystifying Contrastive Self-Supervised Learning: Invariances,
  Augmentations and Dataset Biases
Demystifying Contrastive Self-Supervised Learning: Invariances, Augmentations and Dataset Biases
Senthil Purushwalkam
Abhinav Gupta
SSL
66
213
0
28 Jul 2020
Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning
Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning
Tianlong Chen
Sijia Liu
Shiyu Chang
Yu Cheng
Lisa Amini
Zhangyang Wang
AAML
45
247
0
28 Mar 2020
A Simple Framework for Contrastive Learning of Visual Representations
A Simple Framework for Contrastive Learning of Visual Representations
Ting-Li Chen
Simon Kornblith
Mohammad Norouzi
Geoffrey E. Hinton
SSL
293
18,607
0
13 Feb 2020
ClusterFit: Improving Generalization of Visual Representations
ClusterFit: Improving Generalization of Visual Representations
Xueting Yan
Ishan Misra
Abhinav Gupta
Deepti Ghadiyaram
D. Mahajan
SSL
VLM
86
132
0
06 Dec 2019
Momentum Contrast for Unsupervised Visual Representation Learning
Momentum Contrast for Unsupervised Visual Representation Learning
Kaiming He
Haoqi Fan
Yuxin Wu
Saining Xie
Ross B. Girshick
SSL
145
12,007
0
13 Nov 2019
Accelerating Deep Learning by Focusing on the Biggest Losers
Accelerating Deep Learning by Focusing on the Biggest Losers
Angela H. Jiang
Daniel L.-K. Wong
Giulio Zhou
D. Andersen
J. Dean
...
Gauri Joshi
M. Kaminsky
M. Kozuch
Zachary Chase Lipton
Padmanabhan Pillai
54
120
0
02 Oct 2019
RandAugment: Practical automated data augmentation with a reduced search
  space
RandAugment: Practical automated data augmentation with a reduced search space
E. D. Cubuk
Barret Zoph
Jonathon Shlens
Quoc V. Le
MQ
198
3,458
0
30 Sep 2019
A Closer Look at Domain Shift for Deep Learning in Histopathology
A Closer Look at Domain Shift for Deep Learning in Histopathology
Karin Stacke
Gabriel Eilertsen
Jonas Unger
Claes Lundström
OOD
42
63
0
25 Sep 2019
Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning
Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning
Eric Arazo
Diego Ortego
Paul Albert
Noel E. O'Connor
Kevin McGuinness
101
826
0
08 Aug 2019
Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical
  Position Prediction
Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction
Wenjia Bai
Chen Chen
G. Tarroni
Jinming Duan
Florian Guitton
S. Petersen
Yike Guo
Paul M. Matthews
Daniel Rueckert
SSL
49
179
0
05 Jul 2019
S4L: Self-Supervised Semi-Supervised Learning
S4L: Self-Supervised Semi-Supervised Learning
Xiaohua Zhai
Avital Oliver
Alexander Kolesnikov
Lucas Beyer
SSL
VLM
101
790
0
09 May 2019
On The Power of Curriculum Learning in Training Deep Networks
On The Power of Curriculum Learning in Training Deep Networks
Guy Hacohen
D. Weinshall
ODL
68
443
0
07 Apr 2019
Quantifying the effects of data augmentation and stain color
  normalization in convolutional neural networks for computational pathology
Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology
David Tellez
G. Litjens
Péter Bándi
W. Bulten
J. Bokhorst
F. Ciompi
Jeroen van der Laak
MedIm
OOD
48
478
0
18 Feb 2019
Self-supervised Visual Feature Learning with Deep Neural Networks: A
  Survey
Self-supervised Visual Feature Learning with Deep Neural Networks: A Survey
Longlong Jing
Yingli Tian
SSL
108
1,692
0
16 Feb 2019
Unsupervised Representation Learning by Predicting Image Rotations
Unsupervised Representation Learning by Predicting Image Rotations
Spyros Gidaris
Praveer Singh
N. Komodakis
OOD
SSL
DRL
219
3,272
0
21 Mar 2018
Curriculum Learning by Transfer Learning: Theory and Experiments with
  Deep Networks
Curriculum Learning by Transfer Learning: Theory and Experiments with Deep Networks
D. Weinshall
Gad Cohen
Dan Amir
ODL
42
240
0
11 Feb 2018
Deep Learning for Identifying Metastatic Breast Cancer
Deep Learning for Identifying Metastatic Breast Cancer
Dayong Wang
A. Khosla
Rishab Gargeya
H. Irshad
Andrew H. Beck
MedIm
64
940
0
18 Jun 2016
Unsupervised Learning of Visual Representations by Solving Jigsaw
  Puzzles
Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles
M. Noroozi
Paolo Favaro
SSL
147
2,973
0
30 Mar 2016
Unsupervised Visual Representation Learning by Context Prediction
Unsupervised Visual Representation Learning by Context Prediction
Carl Doersch
Abhinav Gupta
Alexei A. Efros
DRL
SSL
164
2,777
0
19 May 2015
1