Revisiting Robustness in Graph Machine Learning

Revisiting Robustness in Graph Machine Learning

1 May 2023

Stephan Günnemann

Papers citing "Revisiting Robustness in Graph Machine Learning"

7 / 7 papers shown

Title
Optimality of Message-Passing Architectures for Sparse Graphs Aseem Baranwal K. Fountoulakis Aukosh Jagannath 61 11 0 10 Jan 2025
Discrete Randomized Smoothing Meets Quantum Computing Md. Nazmus Sakib Aman Saxena Nicola Franco Md Mashrur Arifin Stephan Günnemann AAML 16 1 0 01 Aug 2024
Explaining the Power of Topological Data Analysis in Graph Machine Learning Funmilola Mary Taiwo Umar Islambekov Cüneyt Gürcan Akçora AI4CE 16 3 0 08 Jan 2024
Assessing Robustness via Score-Based Adversarial Image Generation Marcel Kollovieh Lukas Gosch Yan Scholten Marten Lienen Leo Schwinn Stephan Günnemann DiffM 25 4 0 06 Oct 2023
GraphWorld: Fake Graphs Bring Real Insights for GNNs John Palowitch Anton Tsitsulin Brandon Mayer Bryan Perozzi GNN 177 68 0 28 Feb 2022
Unsolved Problems in ML Safety Dan Hendrycks Nicholas Carlini John Schulman Jacob Steinhardt 156 268 0 28 Sep 2021
Contextual Stochastic Block Models Y. Deshpande Andrea Montanari Elchanan Mossel S. Sen 98 131 0 23 Jul 2018