Random Features Strengthen Graph Neural Networks

8 February 2020

Papers citing "Random Features Strengthen Graph Neural Networks"

50 / 50 papers shown

Title
Towards Invariance to Node Identifiers in Graph Neural Networks Maya Bechler-Speicher Moshe Eliasof Carola-Bibiane Schönlieb Ran Gilad-Bachrach Amir Globerson 56 1 0 20 Feb 2025
Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Nanjangud C. Narendra Nithin Nagaraj OOD CML 39 0 0 23 Jan 2025
Training Hybrid Neural Networks with Multimode Optical Nonlinearities Using Digital Twins Ilker Oguz Louis J. E. Suter J. Hsieh Mustafa Yildirim Niyazi Ulaş Dinç Christophe Moser D. Psaltis 53 2 0 14 Jan 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
Revisiting Random Walks for Learning on Graphs Jinwoo Kim Olga Zaghen Ayhan Suleymanzade Youngmin Ryou Seunghoon Hong 59 0 0 01 Jul 2024
GOAL: A Generalist Combinatorial Optimization Agent Learner Darko Drakulic Sofia Michel J. Andreoli 39 6 0 21 Jun 2024
Contextualized Messages Boost Graph Representations Brian Godwin Lim Galvin Brice Lim Renzo Roel Tan Kazushi Ikeda AI4CE 70 1 0 19 Mar 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
Random Entity Quantization for Parameter-Efficient Compositional Knowledge Graph Representation Jiaang Li Quan Wang Yi Liu L. Zhang Zhendong Mao 27 0 0 24 Oct 2023
How Expressive are Graph Neural Networks in Recommendation? Xuheng Cai Lianghao Xia Xubin Ren Chao Huang 29 6 0 22 Aug 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
Fractional Denoising for 3D Molecular Pre-training Shi Feng Yuyan Ni Yanyan Lan Zhiming Ma Wei-Ying Ma DiffM AI4CE 42 25 0 20 Jul 2023
Expectation-Complete Graph Representations with Homomorphisms Pascal Welke Maximilian Thiessen Fabian Jogl Thomas Gärtner 18 5 0 09 Jun 2023
GeoTMI:Predicting quantum chemical property with easy-to-obtain geometry via positional denoising Hyeonsu Kim Jeheon Woo Seonghwan Kim Seokhyun Moon Jun Hyeong Kim Woo Youn Kim AI4CE 30 6 0 28 Mar 2023
Descriptive complexity for distributed computing with circuits Veeti Ahvonen Damian Heiman L. Hella Antti Kuusisto 22 4 0 08 Mar 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
Equivariant Polynomials for Graph Neural Networks Omri Puny Derek Lim B. Kiani Haggai Maron Y. Lipman 24 31 0 22 Feb 2023
A Theory of Link Prediction via Relational Weisfeiler-Leman on Knowledge Graphs Xingyue Huang Miguel Romero .Ismail .Ilkan Ceylan Pablo Barceló 29 24 0 04 Feb 2023
Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure Ryoma Sato 31 5 0 26 Jan 2023
E(n)-equivariant Graph Neural Cellular Automata G. Gala Daniele Grattarola Erik Quaeghebeur GNN 40 3 0 25 Jan 2023
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
Provably expressive temporal graph networks Amauri Souza Diego Mesquita Samuel Kaski Vikas K. Garg 89 54 0 29 Sep 2022
One Model, Any CSP: Graph Neural Networks as Fast Global Search Heuristics for Constraint Satisfaction Jan Tonshoff Berke Kisin Jakob Lindner Martin Grohe GNN 16 22 0 22 Aug 2022
Universally Expressive Communication in Multi-Agent Reinforcement Learning Matthew Morris Thomas D. Barrett Arnu Pretorius 24 4 0 14 Jun 2022
Shortest Path Networks for Graph Property Prediction Ralph Abboud Radoslav Dimitrov .Ismail .Ilkan Ceylan GNN 27 44 0 02 Jun 2022
Theory of Graph Neural Networks: Representation and Learning Stefanie Jegelka GNN AI4CE 33 68 0 16 Apr 2022
SpeqNets: Sparsity-aware Permutation-equivariant Graph Networks Christopher Morris Gaurav Rattan Sandra Kiefer Siamak Ravanbakhsh 42 39 0 25 Mar 2022
Benchmarking Graphormer on Large-Scale Molecular Modeling Datasets Yu Shi Shuxin Zheng Guolin Ke Yifei Shen Jiacheng You Jiyan He Shengjie Luo Chang-Shu Liu Di He Tie-Yan Liu AI4CE 35 65 0 09 Mar 2022
R-GCN: The R Could Stand for Random Vic Degraeve Gilles Vandewiele F. Ongenae Sofie Van Hoecke GNN 21 13 0 04 Mar 2022
Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks Hongya Wang Haoteng Yin Muhan Zhang Pan Li 35 107 0 01 Mar 2022
A Theoretical Comparison of Graph Neural Network Extensions Pál András Papp Roger Wattenhofer 95 45 0 30 Jan 2022
Equivariant Quantum Graph Circuits Péter Mernyei K. Meichanetzidis .Ismail .Ilkan Ceylan 36 8 0 10 Dec 2021
Node-wise Hardware Trojan Detection Based on Graph Learning Kento Hasegawa Kazuki Yamashita Seira Hidano Kazuhide Fukushima Kazuo Hashimoto N. Togawa 17 24 0 04 Dec 2021
On the Unreasonable Effectiveness of Feature propagation in Learning on Graphs with Missing Node Features Emanuele Rossi Henry Kenlay Maria I. Gorinova B. Chamberlain Xiaowen Dong M. Bronstein 23 87 0 23 Nov 2021
DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks Pál András Papp Karolis Martinkus Lukas Faber Roger Wattenhofer GNN 17 138 0 11 Nov 2021
From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness Lingxiao Zhao Wei Jin L. Akoglu Neil Shah GNN 22 160 0 07 Oct 2021
Equivariant Subgraph Aggregation Networks Beatrice Bevilacqua Fabrizio Frasca Derek Lim Balasubramaniam Srinivasan Chen Cai G. Balamurugan M. Bronstein Haggai Maron 48 174 0 06 Oct 2021
Reconstruction for Powerful Graph Representations Leonardo Cotta Christopher Morris Bruno Ribeiro AI4CE 127 78 0 01 Oct 2021
Learning General Optimal Policies with Graph Neural Networks: Expressive Power, Transparency, and Limits Simon Ståhlberg Blai Bonet Hector Geffner 27 48 0 21 Sep 2021
Graph Neural Networks for Graph Drawing Matteo Tiezzi Gabriele Ciravegna Marco Gori 21 20 0 21 Sep 2021
On Positional and Structural Node Features for Graph Neural Networks on Non-attributed Graphs Hejie Cui Zijie Lu Pan Li Carl Yang 13 80 0 03 Jul 2021
Simple GNN Regularisation for 3D Molecular Property Prediction & Beyond Jonathan Godwin Michael Schaarschmidt Alex Gaunt Alvaro Sanchez-Gonzalez Yulia Rubanova Petar Velivcković J. Kirkpatrick Peter W. Battaglia 33 60 0 15 Jun 2021
Graph Neural Networks with Local Graph Parameters Pablo Barceló Floris Geerts Juan L. Reutter Maksimilian Ryschkov 24 64 0 12 Jun 2021
Breaking the Limits of Message Passing Graph Neural Networks M. Balcilar Pierre Héroux Benoit Gaüzère Pascal Vasseur Sébastien Adam P. Honeine 13 121 0 08 Jun 2021
The Logic of Graph Neural Networks Martin Grohe AI4CE 15 87 0 29 Apr 2021
Combinatorial optimization and reasoning with graph neural networks Quentin Cappart Didier Chételat Elias Boutros Khalil Andrea Lodi Christopher Morris Petar Velickovic AI4CE 32 346 0 18 Feb 2021
Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting Giorgos Bouritsas Fabrizio Frasca S. Zafeiriou M. Bronstein 46 423 0 16 Jun 2020
How hard is to distinguish graphs with graph neural networks? Andreas Loukas GNN 25 6 0 13 May 2020
Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond Fanghui Liu Xiaolin Huang Yudong Chen Johan A. K. Suykens BDL 34 172 0 23 Apr 2020
Principal Neighbourhood Aggregation for Graph Nets Gabriele Corso Luca Cavalleri Dominique Beaini Pietro Lió Petar Velickovic GNN 13 649 0 12 Apr 2020