Invariant and Equivariant Graph Networks

24 December 2018

Papers citing "Invariant and Equivariant Graph Networks"

50 / 134 papers shown

Title
Enhancing Job Salary Prediction with Disentangled Composition Effect Modeling: A Neural Prototyping Approach Yang Ji Ying Sun Hengshu Zhu 46 1 0 17 Mar 2025
Precoder Learning for Weighted Sum Rate Maximization Mingyu Deng Shengqian Han 42 0 0 06 Mar 2025
A Survey of Graph Transformers: Architectures, Theories and Applications Chaohao Yuan Kangfei Zhao Ercan Engin Kuruoglu Liang Wang Tingyang Xu Wenbing Huang Deli Zhao Hong Cheng Yu Rong 57 4 0 23 Feb 2025
Data Augmentation and Regularization for Learning Group Equivariance Oskar Nordenfors Axel Flinth 57 0 0 10 Feb 2025
Graph Counterfactual Explainable AI via Latent Space Traversal Andreas Abildtrup Hansen Paraskevas Pegios Anna Calissano Aasa Feragen OOD BDL AAML 83 0 0 15 Jan 2025
Optimality of Message-Passing Architectures for Sparse Graphs Aseem Baranwal K. Fountoulakis Aukosh Jagannath 81 11 0 10 Jan 2025
Lorentz-Equivariant Quantum Graph Neural Network for High-Energy Physics Md Abrar Jahin Md. Akmol Masud Md Wahiduzzaman Suva M. Mridha Nilanjan Dey 51 1 0 03 Nov 2024
Graph Neural Networks for Edge Signals: Orientation Equivariance and Invariance Dominik Fuchsgruber Tim Poštuvan Stephan Günnemann Simon Geisler 42 2 0 22 Oct 2024
Revisiting Multi-Permutation Equivariance through the Lens of Irreducible Representations Yonatan Sverdlov Ido Springer Nadav Dym 35 2 0 09 Oct 2024
Symmetry-Based Structured Matrices for Efficient Approximately Equivariant Networks Ashwin Samudre Mircea Petrache Brian D. Nord Shubhendu Trivedi 47 2 0 18 Sep 2024
Improving Equivariant Model Training via Constraint Relaxation Stefanos Pertigkiozoglou Evangelos Chatzipantazis Shubhendu Trivedi Kostas Daniilidis 42 4 0 23 Aug 2024
Variational Inference Failures Under Model Symmetries: Permutation Invariant Posteriors for Bayesian Neural Networks Yoav Gelberg Tycho F. A. van der Ouderaa Mark van der Wilk Y. Gal AAML 37 4 0 10 Aug 2024
Neural Networks Trained by Weight Permutation are Universal Approximators Yongqiang Cai Gaohang Chen Zhonghua Qiao 69 1 0 01 Jul 2024
Transport of Algebraic Structure to Latent Embeddings Samuel Pfrommer Brendon G. Anderson Somayeh Sojoudi 37 0 0 27 May 2024
Graph as Point Set Xiyuan Wang Pan Li Muhan Zhang GNN 3DPC PINN 44 4 0 05 May 2024
CSA-Trans: Code Structure Aware Transformer for AST Saeyoon Oh Shin Yoo 41 1 0 07 Apr 2024
On the Theoretical Expressive Power and the Design Space of Higher-Order Graph Transformers Cai Zhou Rose Yu Yusu Wang 41 7 0 04 Apr 2024
On the Completeness of Invariant Geometric Deep Learning Models Zian Li Xiyuan Wang Shijia Kang Muhan Zhang 36 2 0 07 Feb 2024
PF-GNN: Differentiable particle filtering based approximation of universal graph representations Mohammed Haroon Dupty Yanfei Dong W. Lee 26 13 0 31 Jan 2024
Interpreting Equivariant Representations Andreas Abildtrup Hansen Anna Calissano Aasa Feragen 53 1 0 23 Jan 2024
Graph Metanetworks for Processing Diverse Neural Architectures Derek Lim Haggai Maron Marc T. Law Jonathan Lorraine James Lucas AI4CE 34 31 0 07 Dec 2023
A Comparison Between Invariant and Equivariant Classical and Quantum Graph Neural Networks Roy T. Forestano Marçal Comajoan Cara Gopal Ramesh Dahale Zhongtian Dong S. Gleyzer ... Kyoungchul Kong Tom Magorsch Konstantin T. Matchev Katia Matcheva Eyup B. Unlu GNN 29 8 0 30 Nov 2023
Neural Lattice Reduction: A Self-Supervised Geometric Deep Learning Approach G. Marchetti Gabriele Cesa Kumar Pratik Arash Behboodi 37 2 0 14 Nov 2023
Equivariant Deep Weight Space Alignment Aviv Navon Aviv Shamsian Ethan Fetaya Gal Chechik Nadav Dym Haggai Maron 29 21 0 20 Oct 2023
Lie Neurons: Adjoint-Equivariant Neural Networks for Semisimple Lie Algebras Tzu-Yuan Lin Minghan Zhu Maani Ghaffari 48 2 0 06 Oct 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
Graph Automorphism Group Equivariant Neural Networks Edward Pearce-Crump William J. Knottenbelt 26 1 0 15 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 30 0 0 11 Jul 2023
Any-dimensional equivariant neural networks Eitan Levin Mateo Díaz 23 7 0 10 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 46 10 0 05 Jun 2023
Approximation-Generalization Trade-offs under (Approximate) Group Equivariance Mircea Petrache Shubhendu Trivedi 35 22 0 27 May 2023
Investigating how ReLU-networks encode symmetries Georg Bökman Fredrik Kahl 29 6 0 26 May 2023
Making Vision Transformers Truly Shift-Equivariant Renan A. Rojas-Gomez Teck-Yian Lim Minh N. Do Raymond A. Yeh ViT 36 7 0 25 May 2023
Categorification of Group Equivariant Neural Networks Edward Pearce-Crump 22 3 0 27 Apr 2023
An Empirical Study of Realized GNN Expressiveness Yanbo Wang Muhan Zhang 42 10 0 16 Apr 2023
Optimization Dynamics of Equivariant and Augmented Neural Networks Axel Flinth F. Ohlsson 41 5 0 23 Mar 2023
Fast computation of permutation equivariant layers with the partition algebra Charles Godfrey Michael G. Rawson Davis Brown Henry Kvinge 40 6 0 10 Mar 2023
Densely Connected $G$ -invariant Deep Neural Networks with Signed Permutation Representations Devanshu Agrawal James Ostrowski AI4CE 36 0 0 08 Mar 2023
Technical report: Graph Neural Networks go Grammatical Jason Piquenot Aldo Moscatelli Maxime Bérar Pierre Héroux R. Raveaux Jean-Yves Ramel Sébastien Adam 30 1 0 02 Mar 2023
Equivariant Polynomials for Graph Neural Networks Omri Puny Derek Lim B. Kiani Haggai Maron Y. Lipman 28 31 0 22 Feb 2023
Equivariant Architectures for Learning in Deep Weight Spaces Aviv Navon Aviv Shamsian Idan Achituve Ethan Fetaya Gal Chechik Haggai Maron 47 63 0 30 Jan 2023
On the Connection Between MPNN and Graph Transformer Chen Cai Truong Son-Hy Rose Yu Yusu Wang 39 51 0 27 Jan 2023
Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure Ryoma Sato 37 5 0 26 Jan 2023
A Generalization of ViT/MLP-Mixer to Graphs Xiaoxin He Bryan Hooi T. Laurent Adam Perold Yann LeCun Xavier Bresson 47 88 0 27 Dec 2022
Connecting Permutation Equivariant Neural Networks and Partition Diagrams Edward Pearce-Crump 28 9 0 16 Dec 2022
Brauer's Group Equivariant Neural Networks Edward Pearce-Crump AI4CE 13 15 0 16 Dec 2022
Equivariant Networks for Crystal Structures Sekouba Kaba Siamak Ravanbakhsh AI4CE 48 23 0 15 Nov 2022
Unifying O(3) Equivariant Neural Networks Design with Tensor-Network Formalism Zimu Li Zihan Pengmei Han Zheng Erik H. Thiede Junyu Liu Risi Kondor 29 2 0 14 Nov 2022
Boosting the Cycle Counting Power of Graph Neural Networks with I $^2$ -GNNs Yinan Huang Xingang Peng Jianzhu Ma Muhan Zhang 84 47 0 22 Oct 2022
Theoretical Guarantees for Permutation-Equivariant Quantum Neural Networks Louis Schatzki Martín Larocca Quynh T. Nguyen F. Sauvage M. Cerezo 39 84 0 18 Oct 2022