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. 2206.05070
  4. Cited By
Fundamental Limits in Formal Verification of Message-Passing Neural
  Networks
v1v2 (latest)

Fundamental Limits in Formal Verification of Message-Passing Neural Networks

10 June 2022
Marco Sälzer
M. Lange
    GNN
ArXiv (abs)PDFHTML

Papers citing "Fundamental Limits in Formal Verification of Message-Passing Neural Networks"

16 / 16 papers shown
Title
Formal Verification of Graph Convolutional Networks with Uncertain Node Features and Uncertain Graph Structure
Formal Verification of Graph Convolutional Networks with Uncertain Node Features and Uncertain Graph Structure
Tobias Ladner
Michael Eichelbeck
Matthias Althoff
GNN
231
0
0
23 Apr 2024
Reachability Is NP-Complete Even for the Simplest Neural Networks
Reachability Is NP-Complete Even for the Simplest Neural Networks
Marco Sälzer
M. Lange
62
28
0
30 Aug 2021
The Logic of Graph Neural Networks
The Logic of Graph Neural Networks
Martin Grohe
AI4CE
56
92
0
29 Apr 2021
Efficient Robustness Certificates for Discrete Data: Sparsity-Aware
  Randomized Smoothing for Graphs, Images and More
Efficient Robustness Certificates for Discrete Data: Sparsity-Aware Randomized Smoothing for Graphs, Images and More
Aleksandar Bojchevski
Johannes Klicpera
Stephan Günnemann
AAML
94
86
0
29 Aug 2020
Towards More Practical Adversarial Attacks on Graph Neural Networks
Towards More Practical Adversarial Attacks on Graph Neural Networks
Jiaqi Ma
Shuangrui Ding
Qiaozhu Mei
AAML
66
121
0
09 Jun 2020
Scalable Attack on Graph Data by Injecting Vicious Nodes
Scalable Attack on Graph Data by Injecting Vicious Nodes
Jihong Wang
Minnan Luo
Fnu Suya
Jundong Li
Z. Yang
Q. Zheng
AAMLGNN
85
90
0
22 Apr 2020
Indirect Adversarial Attacks via Poisoning Neighbors for Graph
  Convolutional Networks
Indirect Adversarial Attacks via Poisoning Neighbors for Graph Convolutional Networks
Tsubasa Takahashi
GNNAAML
139
37
0
19 Feb 2020
What graph neural networks cannot learn: depth vs width
What graph neural networks cannot learn: depth vs width
Andreas Loukas
GNN
93
301
0
06 Jul 2019
Adversarial Attacks on Graph Neural Networks via Meta Learning
Adversarial Attacks on Graph Neural Networks via Meta Learning
Daniel Zügner
Stephan Günnemann
OODAAMLGNN
134
574
0
22 Feb 2019
Graph Neural Networks for Social Recommendation
Graph Neural Networks for Social Recommendation
Wenqi Fan
Yao Ma
Qing Li
Yuan He
Yue Zhao
Jiliang Tang
Dawei Yin
256
1,909
0
19 Feb 2019
A Comprehensive Survey on Graph Neural Networks
A Comprehensive Survey on Graph Neural Networks
Zonghan Wu
Shirui Pan
Fengwen Chen
Guodong Long
Chengqi Zhang
Philip S. Yu
FaMLGNNAI4TSAI4CE
807
8,597
0
03 Jan 2019
Graph Neural Networks: A Review of Methods and Applications
Graph Neural Networks: A Review of Methods and Applications
Jie Zhou
Ganqu Cui
Shengding Hu
Zhengyan Zhang
Cheng Yang
Zhiyuan Liu
Lifeng Wang
Changcheng Li
Maosong Sun
AI4CEGNN
1.1K
5,551
0
20 Dec 2018
Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks
Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks
Christopher Morris
Martin Ritzert
Matthias Fey
William L. Hamilton
J. E. Lenssen
Gaurav Rattan
Martin Grohe
GNN
194
1,646
0
04 Oct 2018
How Powerful are Graph Neural Networks?
How Powerful are Graph Neural Networks?
Keyulu Xu
Weihua Hu
J. Leskovec
Stefanie Jegelka
GNN
263
7,710
0
01 Oct 2018
Neural Message Passing for Quantum Chemistry
Neural Message Passing for Quantum Chemistry
Justin Gilmer
S. Schoenholz
Patrick F. Riley
Oriol Vinyals
George E. Dahl
598
7,500
0
04 Apr 2017
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Guy Katz
Clark W. Barrett
D. Dill
Kyle D. Julian
Mykel Kochenderfer
AAML
327
1,875
0
03 Feb 2017
1