Provably Powerful Graph Networks

27 May 2019

Papers citing "Provably Powerful Graph Networks"

50 / 119 papers shown

Title
Fourier Sliced-Wasserstein Embedding for Multisets and Measures Tal Amir Nadav Dym 48 2 0 03 Apr 2025
Interpretable High-order Knowledge Graph Neural Network for Predicting Synthetic Lethality in Human Cancers Xuexin Chen Ruichu Cai Zhengting Huang Zijian Li Jie Zheng Min Wu 41 0 0 08 Mar 2025
Towards Graph Foundation Models: A Study on the Generalization of Positional and Structural Encodings Billy Joe Franks Moshe Eliasof Semih Cantürk Guy Wolf Carola-Bibiane Schönlieb Sophie Fellenz Marius Kloft AI4CE 76 0 0 10 Dec 2024
Theoretical Insights into Line Graph Transformation on Graph Learning Fan Yang Xingyue Huang 34 0 0 21 Oct 2024
DMGNN: Detecting and Mitigating Backdoor Attacks in Graph Neural Networks Hao Sui Bing Chen J. Zhang Chengcheng Zhu Di Wu Qinghua Lu Guodong Long AAML 24 1 0 18 Oct 2024
NetDiff: Deep Graph Denoising Diffusion for Ad Hoc Network Topology Generation Félix Marcoccia C. Adjih P. Mühlethaler DiffM 16 0 0 09 Oct 2024
Sampling Foundational Transformer: A Theoretical Perspective Viet Anh Nguyen Minh Lenhat Khoa Nguyen Duong Duc Hieu Dao Huu Hung Truong Son-Hy 44 0 0 11 Aug 2024
Discrete Randomized Smoothing Meets Quantum Computing Md. Nazmus Sakib Aman Saxena Nicola Franco Md Mashrur Arifin Stephan Günnemann AAML 29 1 0 01 Aug 2024
Scalable Graph Compressed Convolutions Junshu Sun Chen Yang Shuhui Wang Qingming Huang GNN 43 0 0 26 Jul 2024
Revisiting Neighborhood Aggregation in Graph Neural Networks for Node Classification using Statistical Signal Processing Mounir Ghogho 35 0 0 21 Jul 2024
Revisiting Random Walks for Learning on Graphs Jinwoo Kim Olga Zaghen Ayhan Suleymanzade Youngmin Ryou Seunghoon Hong 59 0 0 01 Jul 2024
KAGNNs: Kolmogorov-Arnold Networks meet Graph Learning Roman Bresson Giannis Nikolentzos G. Panagopoulos Michail Chatzianastasis Jun Pang Michalis Vazirgiannis 65 42 0 26 Jun 2024
Graph as Point Set Xiyuan Wang Pan Li Muhan Zhang GNN 3DPC PINN 40 4 0 05 May 2024
Neighbour-level Message Interaction Encoding for Improved Representation Learning on Graphs Haimin Zhang Min Xu GNN 34 0 0 15 Apr 2024
On the Theoretical Expressive Power and the Design Space of Higher-Order Graph Transformers Cai Zhou Rose Yu Yusu Wang 32 7 0 04 Apr 2024
Descriptive Kernel Convolution Network with Improved Random Walk Kernel Meng-Chieh Lee Lingxiao Zhao L. Akoglu 18 3 0 08 Feb 2024
On the Completeness of Invariant Geometric Deep Learning Models Zian Li Xiyuan Wang Shijia Kang Muhan Zhang 31 2 0 07 Feb 2024
Interpreting Equivariant Representations Andreas Abildtrup Hansen Anna Calissano Aasa Feragen 45 1 0 23 Jan 2024
Isomorphic-Consistent Variational Graph Auto-Encoders for Multi-Level Graph Representation Learning Hanxuan Yang Qingchao Kong Wenji Mao BDL 13 0 0 09 Dec 2023
Neural Lattice Reduction: A Self-Supervised Geometric Deep Learning Approach G. Marchetti Gabriele Cesa Kumar Pratik Arash Behboodi 29 2 0 14 Nov 2023
D4Explainer: In-Distribution GNN Explanations via Discrete Denoising Diffusion Jialin Chen Shirley Wu Abhijit Gupta Rex Ying DiffM 36 4 0 30 Oct 2023
The Expressive Power of Graph Neural Networks: A Survey Bingxue Zhang Changjun Fan Shixuan Liu Kuihua Huang Xiang Zhao Jin-Yu Huang Zhong Liu 40 19 0 16 Aug 2023
Weisfeiler and Leman Go Measurement Modeling: Probing the Validity of the WL Test Arjun Subramonian Adina Williams Maximilian Nickel Yizhou Sun Levent Sagun 21 0 0 11 Jul 2023
Improving Expressivity of Graph Neural Networks using Localization Anant Kumar Shrutimoy Das Shubhajit Roy Binita Maity Anirban Dasgupta 33 0 0 31 May 2023
A Multidimensional Graph Fourier Transformation Neural Network for Vehicle Trajectory Prediction Marion Neumeier Andreas Tollkühn M. Botsch Wolfgang Utschick 8 5 0 12 May 2023
From Relational Pooling to Subgraph GNNs: A Universal Framework for More Expressive Graph Neural Networks Cai Zhou Xiyuan Wang Muhan Zhang 26 14 0 08 May 2023
Convergence of Message Passing Graph Neural Networks with Generic Aggregation On Large Random Graphs Matthieu Cordonnier Nicolas Keriven Nicolas M Tremblay Samuel Vaiter GNN 49 7 0 21 Apr 2023
An Empirical Study of Realized GNN Expressiveness Yanbo Wang Muhan Zhang 39 10 0 16 Apr 2023
Dynamic Graph Representation Learning with Neural Networks: A Survey Leshanshui Yang Sébastien Adam Clément Chatelain AI4TS AI4CE 34 14 0 12 Apr 2023
Graph Positional Encoding via Random Feature Propagation Moshe Eliasof Fabrizio Frasca Beatrice Bevilacqua Eran Treister Gal Chechik Haggai Maron 22 18 0 06 Mar 2023
Technical report: Graph Neural Networks go Grammatical Jason Piquenot Aldo Moscatelli Maxime Bérar Pierre Héroux R. Raveaux Jean-Yves Ramel Sébastien Adam 25 1 0 02 Mar 2023
Connectivity Optimized Nested Graph Networks for Crystal Structures R. Ruff Patrick Reiser Jan Stuhmer Pascal Friederich GNN 26 10 0 27 Feb 2023
Equivariant Polynomials for Graph Neural Networks Omri Puny Derek Lim B. Kiani Haggai Maron Y. Lipman 24 31 0 22 Feb 2023
Complete Neural Networks for Complete Euclidean Graphs Snir Hordan Tal Amir S. Gortler Nadav Dym 3DPC 24 5 0 31 Jan 2023
Equivariant Architectures for Learning in Deep Weight Spaces Aviv Navon Aviv Shamsian Idan Achituve Ethan Fetaya Gal Chechik Haggai Maron 33 63 0 30 Jan 2023
Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure Ryoma Sato 31 5 0 26 Jan 2023
A Generalization of ViT/MLP-Mixer to Graphs Xiaoxin He Bryan Hooi T. Laurent Adam Perold Yann LeCun Xavier Bresson 33 88 0 27 Dec 2022
On the Ability of Graph Neural Networks to Model Interactions Between Vertices Noam Razin Tom Verbin Nadav Cohen 19 10 0 29 Nov 2022
Beyond 1-WL with Local Ego-Network Encodings Nurudin Alvarez-Gonzalez Andreas Kaltenbrunner Vicencc Gómez 33 5 0 27 Nov 2022
Unifying O(3) Equivariant Neural Networks Design with Tensor-Network Formalism Zimu Li Zihan Pengmei Han Zheng Erik H. Thiede Junyu Liu Risi Kondor 27 2 0 14 Nov 2022
Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks Anders Aamand Justin Y. Chen Piotr Indyk Shyam Narayanan R. Rubinfeld Nicholas Schiefer Sandeep Silwal Tal Wagner 37 21 0 06 Nov 2022
Boosting the Cycle Counting Power of Graph Neural Networks with I $^2$ -GNNs Yinan Huang Xingang Peng Jianzhu Ma Muhan Zhang 81 46 0 22 Oct 2022
Theoretical Guarantees for Permutation-Equivariant Quantum Neural Networks Louis Schatzki Martín Larocca Quynh T. Nguyen F. Sauvage M. Cerezo 27 84 0 18 Oct 2022
Linkless Link Prediction via Relational Distillation Zhichun Guo William Shiao Shichang Zhang Yozen Liu Nitesh V. Chawla Neil Shah Tong Zhao 21 41 0 11 Oct 2022
Generalized energy and gradient flow via graph framelets Andi Han Dai Shi Zhiqi Shao Junbin Gao 70 13 0 08 Oct 2022
Weisfeiler-Lehman goes Dynamic: An Analysis of the Expressive Power of Graph Neural Networks for Attributed and Dynamic Graphs Silvia Beddar-Wiesing Giuseppe Alessio D’Inverno C. Graziani Veronica Lachi Alice Moallemy-Oureh F. Scarselli J. M. Thomas 31 9 0 08 Oct 2022
Diffusion Models for Graphs Benefit From Discrete State Spaces K. Haefeli Karolis Martinkus Nathanael Perraudin Roger Wattenhofer DiffM 85 52 0 04 Oct 2022
Provably expressive temporal graph networks Amauri Souza Diego Mesquita Samuel Kaski Vikas K. Garg 89 54 0 29 Sep 2022
On Representing Linear Programs by Graph Neural Networks Ziang Chen Jialin Liu Xinshang Wang Jian Lu W. Yin AI4CE 57 31 0 25 Sep 2022
Graph neural networks for materials science and chemistry Patrick Reiser Marlen Neubert André Eberhard Luca Torresi Chen Zhou ... Houssam Metni Clint van Hoesel Henrik Schopmans T. Sommer Pascal Friederich GNN AI4CE 39 370 0 05 Aug 2022