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. 2012.12896
  4. Cited By
How Does a Neural Network's Architecture Impact Its Robustness to Noisy
  Labels?

How Does a Neural Network's Architecture Impact Its Robustness to Noisy Labels?

23 December 2020
Jingling Li
Mozhi Zhang
Keyulu Xu
John P. Dickerson
Jimmy Ba
    OOD
    NoLa
ArXivPDFHTML

Papers citing "How Does a Neural Network's Architecture Impact Its Robustness to Noisy Labels?"

5 / 5 papers shown
Title
Strong inductive biases provably prevent harmless interpolation
Strong inductive biases provably prevent harmless interpolation
Michael Aerni
Marco Milanta
Konstantin Donhauser
Fanny Yang
25
9
0
18 Jan 2023
Leveraging Unlabeled Data to Track Memorization
Leveraging Unlabeled Data to Track Memorization
Mahsa Forouzesh
Hanie Sedghi
Patrick Thiran
NoLa
TDI
30
3
0
08 Dec 2022
Curriculum Loss: Robust Learning and Generalization against Label
  Corruption
Curriculum Loss: Robust Learning and Generalization against Label Corruption
Yueming Lyu
Ivor W. Tsang
NoLa
47
170
0
24 May 2019
Representation Learning on Graphs with Jumping Knowledge Networks
Representation Learning on Graphs with Jumping Knowledge Networks
Keyulu Xu
Chengtao Li
Yonglong Tian
Tomohiro Sonobe
Ken-ichi Kawarabayashi
Stefanie Jegelka
GNN
229
1,935
0
09 Jun 2018
Methods for Interpreting and Understanding Deep Neural Networks
Methods for Interpreting and Understanding Deep Neural Networks
G. Montavon
Wojciech Samek
K. Müller
FaML
234
2,231
0
24 Jun 2017
1