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. 2403.04605
  4. Cited By
In-n-Out: Calibrating Graph Neural Networks for Link Prediction

In-n-Out: Calibrating Graph Neural Networks for Link Prediction

7 March 2024
E. Nascimento
Diego Mesquita
Samuel Kaski
Amauri Souza
    UQCV
ArXivPDFHTML

Papers citing "In-n-Out: Calibrating Graph Neural Networks for Link Prediction"

4 / 4 papers shown
Title
Uncertainty Quantification on Graph Learning: A Survey
Uncertainty Quantification on Graph Learning: A Survey
Chao Chen
Chenghua Guo
Rui Xu
Xiangwen Liao
Xi Zhang
Sihong Xie
Hui Xiong
Mohit Bansal
AI4CE
37
1
0
23 Apr 2024
Message passing all the way up
Message passing all the way up
Petar Velickovic
118
64
0
22 Feb 2022
Be Confident! Towards Trustworthy Graph Neural Networks via Confidence
  Calibration
Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration
Xiao Wang
Hongrui Liu
Chuan Shi
Cheng Yang
UQCV
109
116
0
29 Sep 2021
Multi-scale Attributed Node Embedding
Multi-scale Attributed Node Embedding
Benedek Rozemberczki
Carl Allen
Rik Sarkar
GNN
148
838
0
28 Sep 2019
1