Poster "graph neural networks" Papers
208 papers found • Page 4 of 5
Conference
GNNs Also Deserve Editing, and They Need It More Than Once
Shaochen (Henry) Zhong, Duy Le, Zirui Liu et al.
Graph2Tac: Online Representation Learning of Formal Math Concepts
Lasse Blaauwbroek, Mirek Olšák, Jason Rute et al.
Graph As Point Set
Xiyuan Wang, Pan Li, Muhan Zhang
Graph Distillation with Eigenbasis Matching
Yang Liu, Deyu Bo, Chuan Shi
Graph External Attention Enhanced Transformer
Jianqing Liang, Min Chen, Jiye Liang
Graph Mixup on Approximate Gromov–Wasserstein Geodesics
Zhichen Zeng, Ruizhong Qiu, Zhe Xu et al.
Graph Neural Network Causal Explanation via Neural Causal Models
Arman Behnam, Binghui Wang
Graph Neural Network Explanations are Fragile
Jiate Li, Meng Pang, Yun Dong et al.
Graph Neural Networks Use Graphs When They Shouldn't
Maya Bechler-Speicher, Ido Amos, Ran Gilad-Bachrach et al.
Graph Neural Networks with a Distribution of Parametrized Graphs
See Hian Lee, Feng Ji, Kelin Xia et al.
Graph Neural PDE Solvers with Conservation and Similarity-Equivariance
Masanobu Horie, NAOTO MITSUME
Graph Neural Stochastic Diffusion for Estimating Uncertainty in Node Classification
Xixun Lin, Wenxiao Zhang, Fengzhao Shi et al.
Graph Positional and Structural Encoder
Semih Cantürk, Renming Liu, Olivier Lapointe-Gagné et al.
Homomorphism Counts for Graph Neural Networks: All About That Basis
Emily Jin, Michael Bronstein, Ismail Ceylan et al.
How Graph Neural Networks Learn: Lessons from Training Dynamics
Chenxiao Yang, Qitian Wu, David Wipf et al.
Hypergraph-enhanced Dual Semi-supervised Graph Classification
Wei Ju, Zhengyang Mao, Siyu Yi et al.
Learning Divergence Fields for Shift-Robust Graph Representations
Qitian Wu, Fan Nie, Chenxiao Yang et al.
Learning Graph Representation via Graph Entropy Maximization
Ziheng Sun, Xudong Wang, Chris Ding et al.
LLaGA: Large Language and Graph Assistant
Runjin Chen, Tong Zhao, Ajay Jaiswal et al.
MAGNOLIA: Matching Algorithms via GNNs for Online Value-to-go Approximation
Alexandre Hayderi, Amin Saberi, Ellen Vitercik et al.
Mitigating Label Noise on Graphs via Topological Sample Selection
Yuhao Wu, Jiangchao Yao, Xiaobo Xia et al.
Mitigating Oversmoothing Through Reverse Process of GNNs for Heterophilic Graphs
MoonJeong Park, Jaeseung Heo, Dongwoo Kim
Modelling Microbial Communities with Graph Neural Networks
Albane Ruaud, Cansu Sancaktar, Marco Bagatella et al.
Navigating Complexity: Toward Lossless Graph Condensation via Expanding Window Matching
Yuchen Zhang, Tianle Zhang, Kai Wang et al.
Networked Inequality: Preferential Attachment Bias in Graph Neural Network Link Prediction
Arjun Subramonian, Levent Sagun, Yizhou Sun
Neural Sign Actors: A Diffusion Model for 3D Sign Language Production from Text
Vasileios Baltatzis, Rolandos Alexandros Potamias, Evangelos Ververas et al.
Neural SPH: Improved Neural Modeling of Lagrangian Fluid Dynamics
Artur Toshev, Jonas Erbesdobler, Nikolaus Adams et al.
Neural Tangent Kernels Motivate Cross-Covariance Graphs in Neural Networks
Shervin Khalafi, Saurabh Sihag, Alejandro Ribeiro
On dimensionality of feature vectors in MPNNs
César Bravo, Alexander Kozachinskiy, Cristobal Rojas
On the Expressive Power of Spectral Invariant Graph Neural Networks
Bohang Zhang, Lingxiao Zhao, Haggai Maron
On the Generalization of Equivariant Graph Neural Networks
Rafał Karczewski, Amauri Souza, Vikas Garg
On Which Nodes Does GCN Fail? Enhancing GCN From the Node Perspective
Jincheng Huang, Jialie SHEN, Xiaoshuang Shi et al.
Open Ad Hoc Teamwork with Cooperative Game Theory
Jianhong Wang, Yang Li, Yuan Zhang et al.
PAC-Bayesian Generalization Bounds for Knowledge Graph Representation Learning
Jaejun Lee, Minsung Hwang, Joyce Whang
PANDA: Expanded Width-Aware Message Passing Beyond Rewiring
Jeongwhan Choi, Sumin Parksumin, Hyowon Wi et al.
PGODE: Towards High-quality System Dynamics Modeling
Xiao Luo, Yiyang Gu, Huiyu Jiang et al.
PhAST: Physics-Aware, Scalable, and Task-Specific GNNs for Accelerated Catalyst Design
Alexandre Duval, Victor Schmidt, Santiago Miret et al.
POET: Prompt Offset Tuning for Continual Human Action Adaptation
Prachi Garg, Joseph K J, Vineeth N Balasubramanian et al.
Position: Future Directions in the Theory of Graph Machine Learning
Christopher Morris, Fabrizio Frasca, Nadav Dym et al.
Predicting and Interpreting Energy Barriers of Metallic Glasses with Graph Neural Networks
Haoyu Li, Shichang Zhang, Longwen Tang et al.
Predicting Lagrangian Multipliers for Mixed Integer Linear Programs
Francesco Demelas, Joseph Roux, Mathieu Lacroix et al.
Quantum Positional Encodings for Graph Neural Networks
Slimane Thabet, Mehdi Djellabi, Igor Sokolov et al.
Rethinking Independent Cross-Entropy Loss For Graph-Structured Data
Rui Miao, Kaixiong Zhou, Yili Wang et al.
Rethinking Label Poisoning for GNNs: Pitfalls and Attacks
Vijay Chandra Lingam, Mohammad Sadegh Akhondzadeh, Aleksandar Bojchevski
Sign is Not a Remedy: Multiset-to-Multiset Message Passing for Learning on Heterophilic Graphs
Langzhang Liang, Sunwoo Kim, Kijung Shin et al.
Structure Your Data: Towards Semantic Graph Counterfactuals
Angeliki Dimitriou, Maria Lymperaiou, Giorgos Filandrianos et al.
Subgraphormer: Unifying Subgraph GNNs and Graph Transformers via Graph Products
Guy Bar Shalom, Beatrice Bevilacqua, Haggai Maron
Subhomogeneous Deep Equilibrium Models
Pietro Sittoni, Francesco Tudisco
The Expressive Power of Path-Based Graph Neural Networks
Caterina Graziani, Tamara Drucks, Fabian Jogl et al.
The Merit of River Network Topology for Neural Flood Forecasting
Nikolas Kirschstein, Yixuan Sun