v1v2 (latest)

Cayley Graph Propagation

4 October 2024

JJ Wilson

Maya Bechler-Speicher

Petar Veličković

ArXiv (abs)PDF HTML

Papers citing "Cayley Graph Propagation"

50 / 55 papers shown

Title
TxPert: Leveraging Biochemical Relationships for Out-of-Distribution Transcriptomic Perturbation Prediction Frederik Wenkel Wilson Tu Cassandra Masschelein Hamed Shirzad Cian Eastwood ... Jiarui Ding Marta M. Fay Berton Earnshaw Emmanuel Noutahi Alisandra K. Denton OODD 62 1 0 20 May 2025
Schreier-Coset Graph Propagation Aryan Mishra Lizhen Lin 91 0 0 15 May 2025
CayleyPy RL: Pathfinding and Reinforcement Learning on Cayley Graphs A.Chervov A.Soibelman S.Lytkin I.Kiselev S.Fironov ... L.Shishina D.Mamayeva A.Korolkova Kemal Kurniawan A.Romanov 98 0 0 25 Feb 2025
Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks Maya Bechler-Speicher Ben Finkelshtein Fabrizio Frasca Luis Muller Jan Tönshoff ... Michael M. Bronstein Mathias Niepert Bryan Perozzi Mikhail Galkin Christopher Morris OOD 184 6 0 21 Feb 2025
What makes a good feedforward computational graph? Alex Vitvitskyi J. G. Araújo Marc Lackenby Petar Velickovic 113 3 0 10 Feb 2025
Deep Equilibrium Algorithmic Reasoning Dobrik Georgiev JJ Wilson Davide Buffelli Pietro Lio 84 1 0 19 Oct 2024
Commute-Time-Optimised Graphs for GNNs Igor Sterner Shiye Su Petar Velickovic 74 2 0 09 Jul 2024
PANDA: Expanded Width-Aware Message Passing Beyond Rewiring Jeongwhan Choi Sumin Park Hyowon Wi Sung-Bae Cho Noseong Park GNN 91 2 0 06 Jun 2024
Temporal Graph Rewiring with Expander Graphs Katarina Petrović Shenyang Huang Farimah Poursafaei Petar Velickovic AI4CE 93 4 0 04 Jun 2024
Probabilistic Graph Rewiring via Virtual Nodes Chendi Qian Andrei Manolache Christopher Morris Mathias Niepert AI4CE 95 3 0 27 May 2024
Understanding Virtual Nodes: Oversquashing and Node Heterogeneity Joshua Southern Francesco Di Giovanni Michael M. Bronstein J. Lutzeyer 133 1 0 22 May 2024
VN-EGNN: E(3)-Equivariant Graph Neural Networks with Virtual Nodes Enhance Protein Binding Site Identification Florian Sestak Lisa Schneckenreiter Johannes Brandstetter Sepp Hochreiter Andreas Mayr Günter Klambauer 98 11 0 10 Apr 2024
Higher-Order Expander Graph Propagation Thomas Christie Yu He 57 3 0 14 Nov 2023
Exposition on over-squashing problem on GNNs: Current Methods, Benchmarks and Challenges Dai Shi Andi Han Lequan Lin Yi Guo Junbin Gao 82 14 0 13 Nov 2023
Locality-Aware Graph-Rewiring in GNNs Federico Barbero A. Velingker Amin Saberi Michael M. Bronstein Francesco Di Giovanni 84 32 0 02 Oct 2023
Graph Neural Networks Use Graphs When They Shouldn't Maya Bechler-Speicher Ido Amos Ran Gilad-Bachrach Amir Globerson GNN AI4CE 32 15 0 08 Sep 2023
Where Did the Gap Go? Reassessing the Long-Range Graph Benchmark Jan Tönshoff Martin Ritzert Eran Rosenbluth Martin Grohe 81 54 0 01 Sep 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 85 38 0 06 Jun 2023
A Survey on Oversmoothing in Graph Neural Networks T. Konstantin Rusch Michael M. Bronstein Siddhartha Mishra 87 213 0 20 Mar 2023
Exphormer: Sparse Transformers for Graphs Hamed Shirzad A. Velingker B. Venkatachalam Danica J. Sutherland A. Sinop 56 117 0 10 Mar 2023
Understanding Oversquashing in GNNs through the Lens of Effective Resistance Mitchell Black Qingsong Wang A. Nayyeri Yusu Wang 66 68 0 14 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 100 120 0 06 Feb 2023
On the Connection Between MPNN and Graph Transformer Chen Cai Truong-Son Hy Rose Yu Yusu Wang 91 55 0 27 Jan 2023
Revisiting Over-smoothing and Over-squashing Using Ollivier-Ricci Curvature K. Nguyen Hieu Nong T. Nguyen Nhat Ho Khuong N. Nguyen Vinh Phu Nguyen 78 68 0 28 Nov 2022
FoSR: First-order spectral rewiring for addressing oversquashing in GNNs Kedar Karhadkar P. Banerjee Guido Montúfar 77 66 0 21 Oct 2022
Expander Graph Propagation Andreea Deac Marc Lackenby Petar Velivcković 137 56 0 06 Oct 2022
Oversquashing in GNNs through the lens of information contraction and graph expansion P. Banerjee Kedar Karhadkar Yu Guang Wang Uri Alon Guido Montúfar 56 46 0 06 Aug 2022
Understanding convolution on graphs via energies Francesco Di Giovanni J. Rowbottom B. Chamberlain Thomas Markovich Michael M. Bronstein GNN 46 50 0 22 Jun 2022
Long Range Graph Benchmark Vijay Prakash Dwivedi Ladislav Rampášek Mikhail Galkin Alipanah Parviz Guy Wolf Anh Tuan Luu Dominique Beaini 84 218 0 16 Jun 2022
DiffWire: Inductive Graph Rewiring via the Lovász Bound Adrián Arnaiz-Rodríguez Ahmed Begga Francisco Escolano Nuria Oliver 79 67 0 15 Jun 2022
Graph-Coupled Oscillator Networks T. Konstantin Rusch B. Chamberlain J. Rowbottom S. Mishra M. Bronstein 95 115 0 04 Feb 2022
Understanding over-squashing and bottlenecks on graphs via curvature Jake Topping Francesco Di Giovanni B. Chamberlain Xiaowen Dong M. Bronstein 108 448 0 29 Nov 2021
Rethinking Graph Transformers with Spectral Attention Devin Kreuzer Dominique Beaini William L. Hamilton Vincent Létourneau Prudencio Tossou 102 543 0 07 Jun 2021
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges M. Bronstein Joan Bruna Taco S. Cohen Petar Velivcković GNN 358 1,160 0 27 Apr 2021
Design Space for Graph Neural Networks Jiaxuan You Rex Ying J. Leskovec GNN AI4CE 187 321 0 17 Nov 2020
From Local Structures to Size Generalization in Graph Neural Networks Gilad Yehudai Ethan Fetaya E. Meirom Gal Chechik Haggai Maron GNN AI4CE 215 135 0 17 Oct 2020
TUDataset: A collection of benchmark datasets for learning with graphs Christopher Morris Nils M. Kriege Franka Bause Kristian Kersting Petra Mutzel Marion Neumann 239 827 0 16 Jul 2020
Array Programming with NumPy Charles R. Harris K. Millman S. Walt R. Gommers Pauli Virtanen ... Tyler Reddy Warren Weckesser Hameer Abbasi C. Gohlke T. Oliphant 156 14,986 0 18 Jun 2020
On the Bottleneck of Graph Neural Networks and its Practical Implications Uri Alon Eran Yahav GNN 91 694 0 09 Jun 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 309 2,746 0 02 May 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 529 42,559 0 03 Dec 2019
Diffusion Improves Graph Learning Johannes Klicpera Stefan Weißenberger Stephan Günnemann GNN 155 710 0 28 Oct 2019
Revisiting Graph Neural Networks: All We Have is Low-Pass Filters Hoang NT Takanori Maehara GNN 124 434 0 23 May 2019
Fast Graph Representation Learning with PyTorch Geometric Matthias Fey J. E. Lenssen 3DH GNN 3DPC 237 4,361 0 06 Mar 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 783 8,554 0 03 Jan 2019
Graph Neural Networks: A Review of Methods and Applications Jie Zhou Ganqu Cui Shengding Hu Zhengyan Zhang Cheng Yang Zhiyuan Liu Lifeng Wang Changcheng Li Maosong Sun AI4CE GNN 1.1K 5,532 0 20 Dec 2018
How Powerful are Graph Neural Networks? Keyulu Xu Weihua Hu J. Leskovec Stefanie Jegelka GNN 251 7,681 0 01 Oct 2018
Representation Learning on Graphs with Jumping Knowledge Networks Keyulu Xu Chengtao Li Yonglong Tian Tomohiro Sonobe Ken-ichi Kawarabayashi Stefanie Jegelka GNN 516 1,987 0 09 Jun 2018
Relational inductive biases, deep learning, and graph networks Peter W. Battaglia Jessica B. Hamrick V. Bapst Alvaro Sanchez-Gonzalez V. Zambaldi ... Pushmeet Kohli M. Botvinick Oriol Vinyals Yujia Li Razvan Pascanu AI4CE NAI 766 3,129 0 04 Jun 2018
Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning Qimai Li Zhichao Han Xiao-Ming Wu GNN SSL 189 2,828 0 22 Jan 2018