Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks

4 March 2021

Papers citing "Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks"

50 / 159 papers shown

Title
Hodge-Aware Contrastive Learning Alexander Mollers Alexander Immer Vincent Fortuin Elvin Isufi 35 1 0 14 Sep 2023
Generalized Simplicial Attention Neural Networks Claudio Battiloro Lucia Testa Lorenzo Giusti S. Sardellitti P. Lorenzo Sergio Barbarossa 25 18 0 05 Sep 2023
Enhancing Graph Transformers with Hierarchical Distance Structural Encoding Yuan Luo Hongkang Li Lei Shi Xiao-Ming Wu 28 7 0 22 Aug 2023
Topological Graph Signal Compression Guillermo Bernárdez Lev Telyatnikov Eduard Alarcón A. Cabellos-Aparicio Pere Barlet-Ros Pietro Lio' AI4CE 24 0 0 21 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
Weisfeiler and Lehman Go Paths: Learning Topological Features via Path Complexes Quang Truong Peter Chin GNN 27 7 0 13 Aug 2023
XFlow: Benchmarking Flow Behaviors over Graphs Zijian Zhang Zonghan Zhang Zhiqian Chen 38 0 0 07 Aug 2023
Influential Simplices Mining via Simplicial Convolutional Network Yujie Zeng Yiming Huang Qiang Wu Linyuan Lu 21 10 0 11 Jul 2023
Generalization Limits of Graph Neural Networks in Identity Effects Learning Giuseppe Alessio D’Inverno Simone Brugiapaglia Mirco Ravanelli 18 3 0 30 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
Simplicial Message Passing for Chemical Property Prediction Hai Lan Xian Wei 25 0 0 09 Jun 2023
CIN++: Enhancing Topological Message Passing Lorenzo Giusti Teodora Reu Francesco Ceccarelli Cristian Bodnar Pietro Lio' GNN 32 7 0 06 Jun 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 31 85 0 27 May 2023
From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module Claudio Battiloro Indro Spinelli Lev Telyatnikov Michael M. Bronstein Simone Scardapane P. Lorenzo BDL 21 14 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
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
E(n) Equivariant Message Passing Simplicial Networks Floor Eijkelboom Rob D. Hesselink Erik J. Bekkers 22 14 0 11 May 2023
NervePool: A Simplicial Pooling Layer Sarah McGuire E. Munch M. Hirn 33 1 0 10 May 2023
Zoo Guide to Network Embedding Anthony Baptista Rubén J. Sánchez-García A. Baudot Ginestra Bianconi GNN 13 6 0 05 May 2023
Leveraging Label Non-Uniformity for Node Classification in Graph Neural Networks Feng Ji See Hian Lee Hanyang Meng Kai Zhao Jielong Yang Wee Peng Tay 47 12 0 29 Apr 2023
Self-Attention in Colors: Another Take on Encoding Graph Structure in Transformers Romain Menegaux Emmanuel Jehanno Margot Selosse Julien Mairal 23 6 0 21 Apr 2023
What Do GNNs Actually Learn? Towards Understanding their Representations Giannis Nikolentzos Michail Chatzianastasis Michalis Vazirgiannis GNN AI4CE 15 0 0 21 Apr 2023
Architectures of Topological Deep Learning: A Survey of Message-Passing Topological Neural Networks Mathilde Papillon Sophia Sanborn Mustafa Hajij Nina Miolane 3DV AI4CE 30 33 0 20 Apr 2023
Topological Point Cloud Clustering Vincent P. Grande Michael T. Schaub 3DPC 21 7 0 29 Mar 2023
Topological Pooling on Graphs Yuzhou Chen Yulia R. Gel 25 10 0 25 Mar 2023
Tangent Bundle Convolutional Learning: from Manifolds to Cellular Sheaves and Back Claudio Battiloro Zhiyang Wang Hans Riess P. Di Lorenzo Alejandro Ribeiro 33 9 0 20 Mar 2023
Skeleton Regression: A Graph-Based Approach to Estimation with Manifold Structure Zeyu Wei Yen-Chi Chen 32 0 0 19 Mar 2023
An Efficient Subgraph GNN with Provable Substructure Counting Power Zuoyu Yan Junru Zhou Liangcai Gao Zhi Tang Muhan Zhang GNN 29 12 0 19 Mar 2023
Framelet Message Passing Xinliang Liu Bingxin Zhou Chutian Zhang Yu Guang Wang 28 5 0 28 Feb 2023
Equivariant Polynomials for Graph Neural Networks Omri Puny Derek Lim B. Kiani Haggai Maron Y. Lipman 28 31 0 22 Feb 2023
On the Expressivity of Persistent Homology in Graph Learning Bastian Alexander Rieck Bastian Rieck 19 13 0 20 Feb 2023
Is Distance Matrix Enough for Geometric Deep Learning? Zian Li Xiyuan Wang Yinan Huang Muhan Zhang 37 17 0 11 Feb 2023
On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology Francesco Di Giovanni Lorenzo Giusti Federico Barbero Giulia Luise Pietro Lio' Michael M. Bronstein 42 112 0 06 Feb 2023
Curvature Filtrations for Graph Generative Model Evaluation Joshua Southern Jeremy Wayland Michael M. Bronstein Bastian Alexander Rieck 23 14 0 30 Jan 2023
Convolutional Learning on Simplicial Complexes Maosheng Yang Elvin Isufi 21 19 0 26 Jan 2023
WL meet VC Christopher Morris Floris Geerts Jan Tonshoff Martin Grohe 38 27 0 26 Jan 2023
On the Expressive Power of Geometric Graph Neural Networks Chaitanya K. Joshi Cristian Bodnar Simon V. Mathis Taco Cohen Pietro Liò 55 83 0 23 Jan 2023
State of the Art and Potentialities of Graph-level Learning Zhenyu Yang Ge Zhang Jia Wu Jian Yang Quan.Z Sheng ... Charu C. Aggarwal Hao Peng Wenbin Hu Edwin R. Hancock Pietro Lio' GNN AI4CE 35 10 0 14 Jan 2023
Dirac signal processing of higher-order topological signals Lucille Calmon Michael T. Schaub G. Bianconi 19 27 0 12 Jan 2023
t-SMILES: A Scalable Fragment-based Molecular Representation Framework for De Novo Molecule Generation Juan-Ni Wu Tong Wang Yue (Eleanor) Chen Li-Juan Tang Hai-Long Wu Ru-Qin Yu 21 0 0 04 Jan 2023
A Topological Deep Learning Framework for Neural Spike Decoding Edward C. Mitchell Brittany Story D. Boothe P. Franaszczuk Vasileios Maroulas 31 8 0 01 Dec 2022
Graph Convolutional Neural Networks as Parametric CoKleisli morphisms Bruno Gavranović M. Villani GNN 84 0 0 01 Dec 2022
Stable and Transferable Hyper-Graph Neural Networks Mikhail Hayhoe Hans Riess V. Preciado Alejandro Ribeiro 46 1 0 11 Nov 2022
Towards Better Out-of-Distribution Generalization of Neural Algorithmic Reasoning Tasks Sadegh Mahdavi Kevin Swersky Thomas Kipf Milad Hashemi Christos Thrampoulidis Renjie Liao LRM OOD NAI 45 25 0 01 Nov 2022
Improving Graph Neural Networks with Learnable Propagation Operators Moshe Eliasof Lars Ruthotto Eran Treister 34 20 0 31 Oct 2022
Tangent Bundle Filters and Neural Networks: from Manifolds to Cellular Sheaves and Back Claudio Battiloro Zhiyang Wang Hans Riess P. Lorenzo Alejandro Ribeiro 34 13 0 26 Oct 2022
Pooling Strategies for Simplicial Convolutional Networks Domenico Mattia Cinque Claudio Battiloro P. Lorenzo 30 5 0 11 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
Expander Graph Propagation Andreea Deac Marc Lackenby Petar Velivcković 96 52 0 06 Oct 2022
Enumeration of max-pooling responses with generalized permutohedra Laura Escobar Patricio Gallardo Javier González-Anaya J. L. González Guido Montúfar A. Morales 14 1 0 29 Sep 2022