Provably Powerful Graph Networks

27 May 2019

Papers citing "Provably Powerful Graph Networks"

50 / 130 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 41 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 31 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 42 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 39 7 0 04 Apr 2024
Descriptive Kernel Convolution Network with Improved Random Walk Kernel Meng-Chieh Lee Lingxiao Zhao L. Akoglu 21 3 0 08 Feb 2024
On the Completeness of Invariant Geometric Deep Learning Models Zian Li Xiyuan Wang Shijia Kang Muhan Zhang 36 2 0 07 Feb 2024
Pard: Permutation-Invariant Autoregressive Diffusion for Graph Generation Lingxiao Zhao Xueying Ding L. Akoglu DiffM 23 8 0 06 Feb 2024
Interpreting Equivariant Representations Andreas Abildtrup Hansen Anna Calissano Aasa Feragen 50 1 0 23 Jan 2024
Isomorphic-Consistent Variational Graph Auto-Encoders for Multi-Level Graph Representation Learning Hanxuan Yang Qingchao Kong Wenji Mao BDL 20 0 0 09 Dec 2023
Neural Lattice Reduction: A Self-Supervised Geometric Deep Learning Approach G. Marchetti Gabriele Cesa Kumar Pratik Arash Behboodi 34 2 0 14 Nov 2023
D4Explainer: In-Distribution GNN Explanations via Discrete Denoising Diffusion Jialin Chen Shirley Wu Abhijit Gupta Rex Ying DiffM 39 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
Extending the Design Space of Graph Neural Networks by Rethinking Folklore Weisfeiler-Lehman Jiarui Feng Lecheng Kong Hao Liu Dacheng Tao Fuhai Li Muhan Zhang Yixin Chen 44 10 0 05 Jun 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
On Structural Expressive Power of Graph Transformers Wenhao Zhu Tianyu Wen Guojie Song Liangji Wang Bo Zheng 27 15 0 23 May 2023
A Multidimensional Graph Fourier Transformation Neural Network for Vehicle Trajectory Prediction Marion Neumeier Andreas Tollkühn M. Botsch Wolfgang Utschick 19 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 28 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 28 11 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 29 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 41 63 0 30 Jan 2023
Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure Ryoma Sato 34 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 39 88 0 27 Dec 2022
Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs Chenxiao Yang Qitian Wu Jiahua Wang Junchi Yan AI4CE 19 51 0 18 Dec 2022
On the Ability of Graph Neural Networks to Model Interactions Between Vertices Noam Razin Tom Verbin Nadav Cohen 23 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
Comprehensive Analysis of Over-smoothing in Graph Neural Networks from Markov Chains Perspective Weichen Zhao Chenguang Wang Congying Han Tiande Guo 25 1 0 12 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 39 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 84 47 0 22 Oct 2022
Theoretical Guarantees for Permutation-Equivariant Quantum Neural Networks Louis Schatzki Martín Larocca Quynh T. Nguyen F. Sauvage M. Cerezo 34 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