Size-Invariant Graph Representations for Graph Classification Extrapolations

8 March 2021

Papers citing "Size-Invariant Graph Representations for Graph Classification Extrapolations"

50 / 85 papers shown

Title
A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to Adaptation Kexin Zhang Shuhan Liu Song Wang Weili Shi Chen Chen Pan Li Sheng Li Jundong Li Kaize Ding OOD 81 3 0 25 Oct 2024
Neural Networks for Learning Counterfactual G-Invariances from Single Environments S Chandra Mouli Bruno Ribeiro OOD 37 12 0 20 Apr 2021
On the Equivalence Between Temporal and Static Graph Representations for Observational Predictions Jianfei Gao Bruno Ribeiro 44 11 0 12 Mar 2021
Walking Out of the Weisfeiler Leman Hierarchy: Graph Learning Beyond Message Passing Jan Toenshoff Martin Ritzert Hinrikus Wolf Martin Grohe GNN 97 32 0 17 Feb 2021
WILDS: A Benchmark of in-the-Wild Distribution Shifts Pang Wei Koh Shiori Sagawa Henrik Marklund Sang Michael Xie Marvin Zhang ... A. Kundaje Emma Pierson Sergey Levine Chelsea Finn Percy Liang OOD 128 1,406 0 14 Dec 2020
Underspecification Presents Challenges for Credibility in Modern Machine Learning Alexander DÁmour Katherine A. Heller D. Moldovan Ben Adlam B. Alipanahi ... Kellie Webster Steve Yadlowsky T. Yun Xiaohua Zhai D. Sculley OffRL 89 681 0 06 Nov 2020
From Local Structures to Size Generalization in Graph Neural Networks Gilad Yehudai Ethan Fetaya E. Meirom Gal Chechik Haggai Maron GNN AI4CE 189 128 0 17 Oct 2020
The Risks of Invariant Risk Minimization Elan Rosenfeld Pradeep Ravikumar Andrej Risteski OOD 35 307 0 12 Oct 2020
How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks Keyulu Xu Mozhi Zhang Jingling Li S. Du Ken-ichi Kawarabayashi Stefanie Jegelka MLT 61 310 0 24 Sep 2020
GraphCrop: Subgraph Cropping for Graph Classification Yiwei Wang Wei Wang Yuxuan Liang Yujun Cai Bryan Hooi 34 57 0 22 Sep 2020
Representation Learning of Graphs Using Graph Convolutional Multilayer Networks Based on Motifs Xing Li Wei Wei Xiangnan Feng Xue Liu Zhiming Zheng GNN 17 12 0 31 Jul 2020
TUDataset: A collection of benchmark datasets for learning with graphs Christopher Morris Nils M. Kriege Franka Bause Kristian Kersting Petra Mutzel Marion Neumann 111 802 0 16 Jul 2020
Estimating Generalization under Distribution Shifts via Domain-Invariant Representations Ching-Yao Chuang Antonio Torralba Stefanie Jegelka OOD 13 62 0 06 Jul 2020
Causal Feature Selection via Orthogonal Search Ashkan Soleymani Anant Raj Stefan Bauer Bernhard Schölkopf M. Besserve CML 44 17 0 06 Jul 2020
Building powerful and equivariant graph neural networks with structural message-passing Clément Vignac Andreas Loukas P. Frossard 37 119 0 26 Jun 2020
Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting Giorgos Bouritsas Fabrizio Frasca Stefanos Zafeiriou M. Bronstein 78 428 0 16 Jun 2020
Machine Learning on Graphs: A Model and Comprehensive Taxonomy Ines Chami Sami Abu-El-Haija Bryan Perozzi Christopher Ré Kevin Patrick Murphy 62 288 0 07 May 2020
Open Graph Benchmark: Datasets for Machine Learning on Graphs Weihua Hu Matthias Fey Marinka Zitnik Yuxiao Dong Hongyu Ren Bowen Liu Michele Catasta J. Leskovec 147 2,687 0 02 May 2020
Shortcut Learning in Deep Neural Networks Robert Geirhos J. Jacobsen Claudio Michaelis R. Zemel Wieland Brendel Matthias Bethge Felix Wichmann 126 2,023 0 16 Apr 2020
Principal Neighbourhood Aggregation for Graph Nets Gabriele Corso Luca Cavalleri Dominique Beaini Pietro Lio Petar Velickovic GNN 43 659 0 12 Apr 2020
A Survey on The Expressive Power of Graph Neural Networks Ryoma Sato 240 172 0 09 Mar 2020
Directional Message Passing for Molecular Graphs Johannes Klicpera Janek Groß Stephan Günnemann 91 861 0 06 Mar 2020
Out-of-Distribution Generalization via Risk Extrapolation (REx) David M. Krueger Ethan Caballero J. Jacobsen Amy Zhang Jonathan Binas Dinghuai Zhang Rémi Le Priol Aaron Courville OOD 277 921 0 02 Mar 2020
Generalization and Representational Limits of Graph Neural Networks Vikas Garg Stefanie Jegelka Tommi Jaakkola GNN 57 309 0 14 Feb 2020
Can Graph Neural Networks Count Substructures? Zhengdao Chen Lei Chen Soledad Villar Joan Bruna GNN 92 323 0 10 Feb 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 106 42,038 0 03 Dec 2019
Deep Learning for Symbolic Mathematics Guillaume Lample François Charton 3DGS 48 406 0 02 Dec 2019
Causality for Machine Learning Bernhard Schölkopf CML AI4CE LRM 55 455 0 24 Nov 2019
Inductive Relation Prediction by Subgraph Reasoning Komal K. Teru E. Denis William L. Hamilton NAI AI4CE 51 390 0 16 Nov 2019
Hyperbolic Graph Convolutional Neural Networks Ines Chami Rex Ying Christopher Ré J. Leskovec GNN 56 637 0 28 Oct 2019
Hyperbolic Graph Neural Networks Qi Liu Maximilian Nickel Douwe Kiela AI4CE GNN 47 377 0 28 Oct 2019
Neural Execution of Graph Algorithms Petar Velickovic Rex Ying Matilde Padovano R. Hadsell Charles Blundell GNN 53 166 0 23 Oct 2019
Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks Srijan Kumar Xikun Zhang J. Leskovec AI4TS 26 724 0 03 Aug 2019
Invariant Risk Minimization Martín Arjovsky Léon Bottou Ishaan Gulrajani David Lopez-Paz OOD 135 2,190 0 05 Jul 2019
Position-aware Graph Neural Networks Jiaxuan You Rex Ying J. Leskovec 64 492 0 11 Jun 2019
Representation Learning for Dynamic Graphs: A Survey Seyed Mehran Kazemi Rishab Goel Kshitij Jain I. Kobyzev Akshay Sethi Peter Forsyth Pascal Poupart AI4TS AI4CE GNN 68 450 0 27 May 2019
Provably Powerful Graph Networks Haggai Maron Heli Ben-Hamu Hadar Serviansky Y. Lipman 48 575 0 27 May 2019
Analysing Mathematical Reasoning Abilities of Neural Models D. Saxton Edward Grefenstette Felix Hill Pushmeet Kohli LRM 88 420 0 02 Apr 2019
A Survey on Graph Kernels Nils M. Kriege Fredrik D. Johansson Christopher Morris 100 416 0 28 Mar 2019
Relational Pooling for Graph Representations R. Murphy Balasubramaniam Srinivasan Vinayak A. Rao Bruno Ribeiro GNN 55 259 0 06 Mar 2019
Fast Graph Representation Learning with PyTorch Geometric Matthias Fey J. E. Lenssen 3DH GNN 3DPC 128 4,289 0 06 Mar 2019
Link Prediction via Higher-Order Motif Features Ghadeer Abuoda G. D. F. Morales Ashraf Aboulnaga 32 37 0 08 Feb 2019
A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms Yoshua Bengio T. Deleu Nasim Rahaman Nan Rosemary Ke Sébastien Lachapelle O. Bilaniuk Anirudh Goyal C. Pal CML OOD 74 334 0 30 Jan 2019
Heterogeneous Network Motifs Ryan A. Rossi Nesreen Ahmed Aldo G. Carranza David Arbour Anup B. Rao Sungchul Kim Eunyee Koh 36 23 0 28 Jan 2019
A Comprehensive Survey on Graph Neural Networks Zonghan Wu Shirui Pan Fengwen Chen Guodong Long Chengqi Zhang Philip S. Yu FaML GNN AI4TS AI4CE 249 8,441 0 03 Jan 2019
Invariant and Equivariant Graph Networks Haggai Maron Heli Ben-Hamu Nadav Shamir Y. Lipman 48 498 0 24 Dec 2018
Deep Learning on Graphs: A Survey Ziwei Zhang Peng Cui Wenwu Zhu GNN 127 1,324 0 11 Dec 2018
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations Francesco Locatello Stefan Bauer Mario Lucic Gunnar Rätsch Sylvain Gelly Bernhard Schölkopf Olivier Bachem OOD 80 1,451 0 29 Nov 2018
Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks Christopher Morris Martin Ritzert Matthias Fey William L. Hamilton J. E. Lenssen Gaurav Rattan Martin Grohe GNN 114 1,625 0 04 Oct 2018
How Powerful are Graph Neural Networks? Keyulu Xu Weihua Hu J. Leskovec Stefanie Jegelka GNN 115 7,554 0 01 Oct 2018