Theory of Graph Neural Networks: Representation and Learning

16 April 2022

Papers citing "Theory of Graph Neural Networks: Representation and Learning"

50 / 56 papers shown

Title
Parameter-Efficient Conditioning for Material Generalization in Graph-Based Simulators Naveen Raj Manoharan Hassan Iqbal Krishna Kumar AI4CE 96 0 0 07 Nov 2025
On the Convergence and Size Transferability of Continuous-depth Graph Neural Networks Mingsong Yan Charles Kulick Sui Tang 116 0 0 04 Oct 2025
On The Expressive Power of GNN Derivatives Yam Eitan Moshe Eliasof Yoav Gelberg Fabrizio Frasca Guy Bar-Shalom Haggai Maron 110 0 0 02 Oct 2025
What Expressivity Theory Misses: Message Passing Complexity for GNNs Niklas Kemper Tom Wollschlager Stephan Günnemann 130 0 0 01 Sep 2025
On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks Junwei Su Chuan Wu 72 0 0 20 Aug 2025
Exploring Graph-Transformer Out-of-Distribution Generalization Abilities Itay Niv Neta Rabin OOD 93 0 0 25 Jun 2025
Weisfeiler and Leman Go Gambling: Why Expressive Lottery Tickets Win Lorenz Kummer Samir Moustafa Anatol Ehrlich Franka Bause Nikolaus Suess Wilfried Gansterer Nils M. Kriege 148 0 0 04 Jun 2025
Causally Fair Node Classification on Non-IID Graph Data Yucong Dai Jun Liu Yaowei Hu Susan Gauch Yongkai Wu FaML 258 0 0 03 May 2025
Graph neural networks extrapolate out-of-distribution for shortest paths Robert Nerem Samantha Chen Sanjoy Dasgupta Yusu Wang 285 4 0 24 Mar 2025
Performance Heterogeneity in Graph Neural Networks: Lessons for Architecture Design and Preprocessing Lukas Fesser Melanie Weber 163 1 0 01 Mar 2025
Unveiling Mode Connectivity in Graph Neural Networks Bingheng Li Z. Chen Haoyu Han Shenglai Zeng J. Liu Shucheng Zhou 196 1 0 18 Feb 2025
Graph Neural Networks Are More Than Filters: Revisiting and Benchmarking from A Spectral PerspectiveInternational Conference on Learning Representations (ICLR), 2024 Yushun Dong Patrick Soga Yinhan He Song Wang Jundong Li 243 2 0 10 Dec 2024
An Efficient Memory Module for Graph Few-Shot Class-Incremental LearningNeural Information Processing Systems (NeurIPS), 2024 Dong Li Aijia Zhang Junqi Gao Biqing Qi GNN 147 6 0 11 Nov 2024
Enhancing Missing Data Imputation through Combined Bipartite Graph and Complete Directed Graph Zhaoyang Zhang Hongtu Zhu Ziqi Chen Yingjie Zhang Hai Shu 220 0 0 07 Nov 2024
Deeper Insights into Deep Graph Convolutional Networks: Stability and GeneralizationIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024 Guangrui Yang Ming Li Han Feng Xiaosheng Zhuang GNN OOD BDL 190 3 0 11 Oct 2024
The Role of Fibration Symmetries in Geometric Deep Learning Osvaldo Velarde Lucas Parra Paolo Boldi Hernan Makse FedML AI4CE 186 2 0 28 Aug 2024
Graph Classification with GNNs: Optimisation, Representation and Inductive BiasEuropean Conference on Artificial Intelligence (ECAI), 2024 P. Krishna Kumar a H. G. Ramaswamy 198 0 0 17 Aug 2024
What Ails Generative Structure-based Drug Design: Expressivity is Too Little or Too Much?International Conference on Artificial Intelligence and Statistics (AISTATS), 2024 Rafał Karczewski Samuel Kaski Markus Heinonen Vikas Garg 285 0 0 12 Aug 2024
Foundations and Frontiers of Graph Learning Theory Yu Huang Min Zhou Menglin Yang Zhen Wang Muhan Zhang Jie Wang Hong Xie Hao Wang Defu Lian Enhong Chen AI4CE GNN 335 5 0 03 Jul 2024
Training-free Graph Neural Networks and the Power of Labels as Features Ryoma Sato 248 5 0 30 Apr 2024
DE-HNN: An effective neural model for Circuit Netlist representation Zhishang Luo Truong-Son Hy Puoya Tabaghi Donghyeon Koh Michael Defferrard Elahe Rezaei Ryan Carey William Rhett Davis Rajeev Jain Yusu Wang 228 9 0 30 Mar 2024
Rethinking the Capacity of Graph Neural Networks for Branching StrategyNeural Information Processing Systems (NeurIPS), 2024 Ziang Chen Jialin Liu Xiaohan Chen Xinshang Wang Wotao Yin 347 9 0 11 Feb 2024
Future Directions in the Theory of Graph Machine Learning Christopher Morris Fabrizio Frasca Nadav Dym Haggai Maron .Ismail .Ilkan Ceylan Ron Levie Derek Lim Michael M. Bronstein Martin Grohe Stefanie Jegelka AI4CE 483 7 0 03 Feb 2024
Precedence-Constrained Winter Value for Effective Graph Data Valuation Hongliang Chi Wei Jin Charu C. Aggarwal Yao Ma 115 5 0 02 Feb 2024
Attacking Graph Neural Networks with Bit Flips: Weisfeiler and Lehman Go Indifferent Lorenz Kummer Samir Moustafa Nils N. Kriege Wilfried N. Gansterer GNN AAML 165 0 0 02 Nov 2023
Are GATs Out of Balance?Neural Information Processing Systems (NeurIPS), 2023 Nimrah Mustafa Aleksandar Bojchevski R. Burkholz 294 8 0 11 Oct 2023
Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient MethodsNeural Information Processing Systems (NeurIPS), 2023 Constantine Caramanis Eleni Psaroudaki Alkis Kalavasis Vasilis Kontonis Christos Tzamos 230 5 0 08 Oct 2023
How Graph Neural Networks Learn: Lessons from Training DynamicsInternational Conference on Machine Learning (ICML), 2023 Chenxiao Yang Qitian Wu David Wipf Ruoyu Sun Junchi Yan AI4CE GNN 390 2 0 08 Oct 2023
On the Two Sides of Redundancy in Graph Neural Networks Vidya Sagar Sharma Samir Moustafa Johannes Langguth Wilfried N. Gansterer Nils M. Kriege 235 2 0 06 Oct 2023
On the Robustness of Post-hoc GNN Explainers to Label Noise Zhiqiang Zhong Yangqianzi Jiang Davide Mottin AAML NoLa 156 3 0 04 Sep 2023
A Survey of Graph Unlearning Anwar Said Hanyu Wang Yuying Zhao Tyler Derr Mudassir Shabbir W. Abbas X. Koutsoukos MU 374 11 0 23 Aug 2023
Learning Resource Allocation Policy: Vertex-GNN or Edge-GNN?IEEE Transactions on Machine Learning in Communications and Networking (IEEE TMLCN), 2023 Yao Peng Jia Guo Chenyang Yang 222 28 0 24 Jul 2023
What can a Single Attention Layer Learn? A Study Through the Random Features LensNeural Information Processing Systems (NeurIPS), 2023 Hengyu Fu Tianyu Guo Yu Bai Song Mei MLT 169 34 0 21 Jul 2023
On the power of graph neural networks and the role of the activation function Sammy Khalife A. Basu 342 9 0 10 Jul 2023
Limits, approximation and size transferability for GNNs on sparse graphs via graphopsNeural Information Processing Systems (NeurIPS), 2023 Thien Le Stefanie Jegelka 120 13 0 07 Jun 2023
Learning to Extrapolate: A Transductive ApproachInternational Conference on Learning Representations (ICLR), 2023 Aviv Netanyahu Abhishek Gupta Max Simchowitz Jianchao Tan Pulkit Agrawal 219 19 0 27 Apr 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 436 12 0 21 Apr 2023
Descriptive complexity for distributed computing with circuitsInternational Symposium on Mathematical Foundations of Computer Science (MFCS), 2023 Veeti Ahvonen Damian Heiman L. Hella Antti Kuusisto 199 4 0 08 Mar 2023
Neural Algorithmic Reasoning with Causal RegularisationInternational Conference on Machine Learning (ICML), 2023 Beatrice Bevilacqua Kyriacos Nikiforou Borja Ibarz Ioana Bica Michela Paganini Charles Blundell Jovana Mitrović Petar Velivcković OOD CML NAI 311 34 0 20 Feb 2023
Knowledge-augmented Graph Machine Learning for Drug Discovery: A Survey from Precision to InterpretabilityACM Computing Surveys (ACM Comput. Surv.), 2023 Zhiqiang Zhong A. Barkova Davide Mottin 162 11 0 16 Feb 2023
Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph DiffusionInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023 Haotian Ju Dongyue Li Aneesh Sharma Hongyang R. Zhang 222 45 0 09 Feb 2023
On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and TopologyInternational Conference on Machine Learning (ICML), 2023 Francesco Di Giovanni Lorenzo Giusti Federico Barbero Giulia Luise Pietro Lio Michael M. Bronstein 337 165 0 06 Feb 2023
Graph Neural Networks can Recover the Hidden Features Solely from the Graph StructureInternational Conference on Machine Learning (ICML), 2023 Ryoma Sato 302 8 0 26 Jan 2023
On the Expressive Power of Geometric Graph Neural NetworksInternational Conference on Machine Learning (ICML), 2023 Chaitanya K. Joshi Cristian Bodnar Simon Mathis Taco Cohen Pietro Liò 355 113 0 23 Jan 2023
Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural NetworksNeural Information Processing Systems (NeurIPS), 2022 Anders Aamand Justin Y. Chen Piotr Indyk Shyam Narayanan R. Rubinfeld Nicholas Schiefer Sandeep Silwal Tal Wagner 224 25 0 06 Nov 2022
On Classification Thresholds for Graph Attention with Edge Features Kimon Fountoulakis Dake He Silvio Lattanzi Bryan Perozzi Anton Tsitsulin Shenghao Yang GNN 235 6 0 18 Oct 2022
Analysis of Convolutions, Non-linearity and Depth in Graph Neural Networks using Neural Tangent Kernel Mahalakshmi Sabanayagam Pascal Esser Debarghya Ghoshdastidar 281 3 0 18 Oct 2022
Theory for Equivariant Quantum Neural NetworksPRX Quantum (PRX Quantum), 2022 Quynh T. Nguyen Louis Schatzki Paolo Braccia Michael Ragone Patrick J. Coles F. Sauvage Martín Larocca M. Cerezo 243 111 0 16 Oct 2022
Weisfeiler-Lehman goes Dynamic: An Analysis of the Expressive Power of Graph Neural Networks for Attributed and Dynamic GraphsNeural Networks (NN), 2022 Silvia Beddar-Wiesing Giuseppe Alessio D’Inverno C. Graziani Veronica Lachi Alice Moallemy-Oureh F. Scarselli J. M. Thomas 225 13 0 08 Oct 2022
Tree Mover's Distance: Bridging Graph Metrics and Stability of Graph Neural NetworksNeural Information Processing Systems (NeurIPS), 2022 Ching-Yao Chuang Stefanie Jegelka OOD 160 43 0 04 Oct 2022