Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks

4 October 2018

Papers citing "Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks"

50 / 808 papers shown

Title
Learning Universal and Robust 3D Molecular Representations with Graph Convolutional Networks Shuo-feng Zhang Yang Liu Li Xie Lei Xie 3DV 16 0 0 24 Jul 2023
A Multi-Task Perspective for Link Prediction with New Relation Types and Nodes Jincheng Zhou Beatrice Bevilacqua Bruno Ribeiro 27 7 0 12 Jul 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
On the power of graph neural networks and the role of the activation function Sammy Khalife A. Basu 24 7 0 10 Jul 2023
Graph Convolutional Networks for Simulating Multi-phase Flow and Transport in Porous Media Jiamin Jiang B. Guo GNN AI4CE 19 0 0 10 Jul 2023
Polynomial Width is Sufficient for Set Representation with High-dimensional Features Peihao Wang Shenghao Yang Shu Li Zhangyang Wang Pan Li 19 3 0 08 Jul 2023
A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks Vignesh Kothapalli Tom Tirer Joan Bruna 34 10 0 04 Jul 2023
SwinGNN: Rethinking Permutation Invariance in Diffusion Models for Graph Generation Qi Yan Zhen-Long Liang Yang Song Renjie Liao Lele Wang DiffM 52 18 0 04 Jul 2023
PlanE: Representation Learning over Planar Graphs Radoslav Dimitrov Zeyang Zhao Ralph Abboud .Ismail .Ilkan Ceylan GNN 29 9 0 03 Jul 2023
Automatic MILP Solver Configuration By Learning Problem Similarities Abdelrahman I. Hosny Sherief Reda 32 4 0 02 Jul 2023
Generalization Limits of Graph Neural Networks in Identity Effects Learning Giuseppe Alessio D’Inverno Simone Brugiapaglia Mirco Ravanelli 13 3 0 30 Jun 2023
Graphtester: Exploring Theoretical Boundaries of GNNs on Graph Datasets Eren Akbiyik Florian Grötschla Béni Egressy Roger Wattenhofer 19 2 0 30 Jun 2023
Interpretable Sparsification of Brain Graphs: Better Practices and Effective Designs for Graph Neural Networks Gao Li M. Duda X. Zhang Danai Koutra Yujun Yan 13 8 0 26 Jun 2023
Generalised f-Mean Aggregation for Graph Neural Networks Ryan Kortvelesy Steven D. Morad Amanda Prorok FedML AI4CE 17 4 0 24 Jun 2023
Provably Powerful Graph Neural Networks for Directed Multigraphs Béni Egressy Luc von Niederhäusern Jovan Blanusa Erik Altman Roger Wattenhofer Kubilay Atasu 25 15 0 20 Jun 2023
P-tensors: a General Formalism for Constructing Higher Order Message Passing Networks Tianyi Sun Andrew R. Hands Risi Kondor 18 2 0 19 Jun 2023
Advancing Biomedicine with Graph Representation Learning: Recent Progress, Challenges, and Future Directions Fang Li Yi Nian Zenan Sun Cui Tao LM&MA OOD AI4TS AI4CE 28 5 0 18 Jun 2023
3D molecule generation by denoising voxel grids Pedro H. O. Pinheiro Joshua Rackers J. Kleinhenz Michael R. Maser Omar Mahmood Andrew Watkins Stephen Ra Vishnu Sresht Saeed Saremi DiffM 34 20 0 13 Jun 2023
Neural Injective Functions for Multisets, Measures and Graphs via a Finite Witness Theorem Tal Amir S. Gortler Ilai Avni Ravi Ravina Nadav Dym 97 23 0 10 Jun 2023
NeuroGraph: Benchmarks for Graph Machine Learning in Brain Connectomics Anwar Said Roza G. Bayrak Tyler Derr Mudassir Shabbir Daniel Moyer Catie Chang X. Koutsoukos 20 25 0 09 Jun 2023
Path Neural Networks: Expressive and Accurate Graph Neural Networks Gaspard Michel Giannis Nikolentzos J. Lutzeyer Michalis Vazirgiannis GNN 18 26 0 09 Jun 2023
Expectation-Complete Graph Representations with Homomorphisms Pascal Welke Maximilian Thiessen Fabian Jogl Thomas Gärtner 18 6 0 09 Jun 2023
Complexity-aware Large Scale Origin-Destination Network Generation via Diffusion Model Can Rong Jingtao Ding Zhicheng Liu Yong Li DiffM 11 7 0 08 Jun 2023
Learning to Navigate in Turbulent Flows with Aerial Robot Swarms: A Cooperative Deep Reinforcement Learning Approach Diego Patiño Siddharth Mayya J. Calderon Kostas Daniilidis David Saldaña 22 3 0 07 Jun 2023
Limits, approximation and size transferability for GNNs on sparse graphs via graphops Thien Le Stefanie Jegelka 27 10 0 07 Jun 2023
Fine-grained Expressivity of Graph Neural Networks Jan Böker Ron Levie Ningyuan Huang Soledad Villar Christopher Morris 28 20 0 06 Jun 2023
How does over-squashing affect the power of GNNs? Francesco Di Giovanni T. Konstantin Rusch Michael M. Bronstein Andreea Deac Marc Lackenby Siddhartha Mishra Petar Velivcković 30 34 0 06 Jun 2023
CIN++: Enhancing Topological Message Passing Lorenzo Giusti Teodora Reu Francesco Ceccarelli Cristian Bodnar Pietro Lio' GNN 32 7 0 06 Jun 2023
GRAFENNE: Learning on Graphs with Heterogeneous and Dynamic Feature Sets Shubham Gupta S. Manchanda Sayan Ranu Srikanta J. Bedathur 22 7 0 06 Jun 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
Representational Strengths and Limitations of Transformers Clayton Sanford Daniel J. Hsu Matus Telgarsky 22 81 0 05 Jun 2023
Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance Jinwoo Kim Tien Dat Nguyen Ayhan Suleymanzade Hyeokjun An Seunghoon Hong 50 23 0 05 Jun 2023
There is more to graphs than meets the eye: Learning universal features with self-supervision L. Das Sai Munikoti M. Halappanavar SSL OOD 22 1 0 31 May 2023
Symmetry-Aware Robot Design with Structured Subgroups Heng Dong Junyu Zhang Tonghan Wang Chongjie Zhang 27 10 0 31 May 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 the Correspondence Between Monotonic Max-Sum GNNs and Datalog David Tena Cucala Bernardo Cuenca Grau B. Motik Egor V. Kostylev 22 8 0 29 May 2023
Graph Inductive Biases in Transformers without Message Passing Liheng Ma Chen Lin Derek Lim Adriana Romero Soriano P. Dokania Mark J. Coates Philip H. S. Torr Ser-Nam Lim AI4CE 24 85 0 27 May 2023
A graphon-signal analysis of graph neural networks Ron Levie 26 17 0 25 May 2023
Union Subgraph Neural Networks Jiaxing Xu Aihu Zhang Qingtian Bian Vijay Prakash Dwivedi Yiping Ke GNN 27 6 0 25 May 2023
Revisiting Generalized p-Laplacian Regularized Framelet GCNs: Convergence, Energy Dynamic and Training with Non-Linear Diffusion Dai Shi Zhiqi Shao Yi Guo Qianchuan Zhao Junbin Gao 34 1 0 25 May 2023
On Structural Expressive Power of Graph Transformers Wenhao Zhu Tianyu Wen Guojie Song Liangji Wang Bo Zheng 25 15 0 23 May 2023
Link Prediction without Graph Neural Networks Zexi Huang Mert Kosan A. Silva Ambuj K. Singh 54 3 0 23 May 2023
GraphMoco:a Graph Momentum Contrast Model that Using Multimodel Structure Information for Large-scale Binary Function Representation Learning Runjin Sun Shize Guo Wei Li XingYu Zhang Xi Guo Zhisong Pan 27 4 0 18 May 2023
Edge Directionality Improves Learning on Heterophilic Graphs Emanuele Rossi Bertrand Charpentier Francesco Di Giovanni Fabrizio Frasca Stephan Günnemann Michael M. Bronstein 22 56 0 17 May 2023
AGFormer: Efficient Graph Representation with Anchor-Graph Transformer Bo Jiang Fei Xu Ziyan Zhang Jin Tang Feiping Nie 31 4 0 12 May 2023
E(n) Equivariant Message Passing Simplicial Networks Floor Eijkelboom Rob D. Hesselink Erik J. Bekkers 20 14 0 11 May 2023
Towards Better Graph Representation Learning with Parameterized Decomposition & Filtering Mingqi Yang Wenjie Feng Yanming Shen Bryan Hooi 30 5 0 10 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
Segmentation and Vascular Vectorization for Coronary Artery by Geometry-based Cascaded Neural Network Xiaoyu Yang Lijian Xu Simon Yu Qing Xia Hongsheng Li Shaoting Zhang 22 4 0 07 May 2023
BitGNN: Unleashing the Performance Potential of Binary Graph Neural Networks on GPUs Jou-An Chen Hsin-Hsuan Sung Xipeng Shen Sutanay Choudhury Ang Li GNN MQ 26 6 0 04 May 2023