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. 1910.00324
  4. Cited By
Graph convolutional networks for learning with few clean and many noisy
  labels

Graph convolutional networks for learning with few clean and many noisy labels

1 October 2019
Ahmet Iscen
Giorgos Tolias
Yannis Avrithis
Ondřej Chum
Cordelia Schmid
    SSL
ArXivPDFHTML

Papers citing "Graph convolutional networks for learning with few clean and many noisy labels"

6 / 6 papers shown
Title
Noise-Tolerant Hybrid Prototypical Learning with Noisy Web Data
Chao Liang
Linchao Zhu
Zongxin Yang
Wei Chen
Yi Yang
NoLa
66
0
0
05 Jan 2025
Learning with Neighbor Consistency for Noisy Labels
Learning with Neighbor Consistency for Noisy Labels
Ahmet Iscen
Jack Valmadre
Anurag Arnab
Cordelia Schmid
NoLa
41
75
0
04 Feb 2022
Generalized Jensen-Shannon Divergence Loss for Learning with Noisy
  Labels
Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels
Erik Englesson
Hossein Azizpour
NoLa
34
104
0
10 May 2021
Probabilistic Model-Agnostic Meta-Learning
Probabilistic Model-Agnostic Meta-Learning
Chelsea Finn
Kelvin Xu
Sergey Levine
BDL
176
666
0
07 Jun 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
413
11,715
0
09 Mar 2017
Geometric deep learning: going beyond Euclidean data
Geometric deep learning: going beyond Euclidean data
M. Bronstein
Joan Bruna
Yann LeCun
Arthur Szlam
P. Vandergheynst
GNN
261
3,243
0
24 Nov 2016
1