Graph Attention

Benchmarks archive 2025-07-28

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Libraries

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Datasets archive 2025-07-28

1 dataset whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

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Most implemented papers archive 2025-07-28

30 shown of 413 papers with code (1,088 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Graph Attention Networks
  30 Oct 2017 93 repositories listed Syntology ran 50 of 106 samples · 56 unverified · 43 pointer-only (licence)
  We present graph attention networks (GATs), novel neural network architectures that operate on graph-structured data, leveraging masked self-attentional layers to address the shortcomings of prior methods based on graph…
• How Attentive are Graph Attention Networks?
  30 May 2021 8 repositories listed Syntology ran 6 of 16 samples · 10 unverified · 1 pointer-only (licence)
  Because GATs use a static attention mechanism, there are simple graph problems that GAT cannot express: in a controlled problem, we show that static attention hinders GAT from even fitting the training data.
• GraphSAINT: Graph Sampling Based Inductive Learning Method
  10 Jul 2019 8 repositories listed
  Graph Convolutional Networks (GCNs) are powerful models for learning representations of attributed graphs.
• Inductive Representation Learning on Temporal Graphs
  19 Feb 2020 5 repositories listed Syntology ran 0 of 1 samples · 1 unverified · 1 pointer-only (licence)
  Moreover, node and topological features can be temporal as well, whose patterns the node embeddings should also capture.
• Graph Neural Networks: A Review of Methods and Applications
  20 Dec 2018 5 repositories listed
  Lots of learning tasks require dealing with graph data which contains rich relation information among elements.
• Representation Learning on Graphs with Jumping Knowledge Networks
  9 Jun 2018 5 repositories listed Syntology ran 0 of 1 samples · 1 unverified
  Furthermore, combining the JK framework with models like Graph Convolutional Networks, GraphSAGE and Graph Attention Networks consistently improves those models' performance.
• Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs
  23 Jun 2022 4 repositories listed Syntology ran 3 of 4 samples · 1 unverified
  Despite their widespread success in various domains, Transformer networks have yet to perform well across datasets in the domain of 3D atomistic graphs such as molecules even when 3D-related inductive biases like…
• Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery
  4 Jun 2021 4 repositories listed Syntology ran 0 of 14 samples · 14 unverified
  We developed Distilled Graph Attention Policy Network (DGAPN), a reinforcement learning model to generate novel graph-structured chemical representations that optimize user-defined objectives by efficiently navigating a…
• Graph Neural Network for Traffic Forecasting: A Survey
  27 Jan 2021 4 repositories listed
  In recent years, to model the graph structures in transportation systems as well as contextual information, graph neural networks have been introduced and have achieved state-of-the-art performance in a series of…
• Visual-Semantic Graph Attention Networks for Human-Object Interaction Detection
  7 Jan 2020 4 repositories listed
  Few works have studied the disambiguating contribution of subsidiary relations made available via graph networks.
• MEGAN: Multi-Explanation Graph Attention Network
  23 Nov 2022 3 repositories listed
  Unlike existing graph explainability methods, our network can produce node and edge attributional explanations along multiple channels, the number of which is independent of task specifications.
• RAGA: Relation-aware Graph Attention Networks for Global Entity Alignment
  1 Mar 2021 3 repositories listed
  Entity alignment (EA) is the task to discover entities referring to the same real-world object from different knowledge graphs (KGs), which is the most crucial step in integrating multi-source KGs.
• HATS: A Hierarchical Graph Attention Network for Stock Movement Prediction
  7 Aug 2019 3 repositories listed
  Methods that use relational data for stock market prediction have been recently proposed, but they are still in their infancy.
• GAPNet: Graph Attention based Point Neural Network for Exploiting Local Feature of Point Cloud
  21 May 2019 3 repositories listed
  In this paper, we propose a novel neural network for point cloud, dubbed GAPNet, to learn local geometric representations by embedding graph attention mechanism within stacked Multi-Layer-Perceptron (MLP) layers.
• Graph Matching Networks for Learning the Similarity of Graph Structured Objects
  29 Apr 2019 3 repositories listed
  This paper addresses the challenging problem of retrieval and matching of graph structured objects, and makes two key contributions.
• PLDR-LLM: Large Language Model from Power Law Decoder Representations
  22 Oct 2024 2 repositories listed
  We present the Large Language Model from Power Law Decoder Representations (PLDR-LLM), a language model that leverages non-linear and linear transformations through Power Law Graph Attention mechanism to generate…
• scVGAE: A Novel Approach using ZINB-Based Variational Graph Autoencoder for Single-Cell RNA-Seq Imputation
  13 Mar 2024 2 repositories listed
  Consequently, methods have been developed to model the data according to this distribution.
• Temporal and Heterogeneous Graph Neural Network for Financial Time Series Prediction
  9 May 2023 2 repositories listed
  The price movement prediction of stock market has been a classical yet challenging problem, with the attention of both economists and computer scientists.
• Transposed Variational Auto-encoder with Intrinsic Feature Learning for Traffic Forecasting
  30 Oct 2022 2 repositories listed
  In this technical report, we present our solutions to the Traffic4cast 2022 core challenge and extended challenge.
• How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision
  11 Apr 2022 2 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  However, what graph attention learns is not understood well, particularly when graphs are noisy.
• Global-Reasoned Multi-Task Learning Model for Surgical Scene Understanding
  28 Jan 2022 2 repositories listed Syntology ran 1 of 8 samples · 7 unverified · 8 pointer-only (licence)
  Global and local relational reasoning enable scene understanding models to perform human-like scene analysis and understanding.
• Multi-task Joint Strategies of Self-supervised Representation Learning on Biomedical Networks for Drug Discovery
  12 Jan 2022 2 repositories listed
  Therefore, we conjecture that the multimodal and local-global combination strategies can be treated as the guideline of multi-task SSL for drug discovery.
• FRT-PAD: Effective Presentation Attack Detection Driven by Face Related Task
  22 Nov 2021 2 repositories listed
  The proposed method, first introduces task specific features from other face related task, then, we design a Cross-Modal Adapter using a Graph Attention Network (GAT) to re-map such features to adapt to PAD task.
• AASIST: Audio Anti-Spoofing using Integrated Spectro-Temporal Graph Attention Networks
  4 Oct 2021 2 repositories listed Syntology ran 11 of 12 samples · 1 unverified
  Artefacts that differentiate spoofed from bona-fide utterances can reside in spectral or temporal domains.
• DisenKGAT: Knowledge Graph Embedding with Disentangled Graph Attention Network
  22 Aug 2021 2 repositories listed
  Knowledge graph completion (KGC) has become a focus of attention across deep learning community owing to its excellent contribution to numerous downstream tasks.
• DeepDDS: deep graph neural network with attention mechanism to predict synergistic drug combinations
  6 Jul 2021 2 repositories listed
  Therefore, computational screening has become an important way to prioritize drug combinations.
• Customizing Graph Neural Networks using Path Reweighting
  21 Jun 2021 2 repositories listed
  Specifically, the proposed CustomGNN can automatically learn the high-level semantics for specific downstream tasks to highlight semantically relevant paths as well to filter out task-irrelevant noises in a graph.
• GIPA: General Information Propagation Algorithm for Graph Learning
  13 May 2021 2 repositories listed
  Graph neural networks (GNNs) have been popularly used in analyzing graph-structured data, showing promising results in various applications such as node classification, link prediction and network recommendation.
• Multivariate Time-series Anomaly Detection via Graph Attention Network
  4 Sep 2020 2 repositories listed Syntology ran 3 of 8 samples · 5 unverified
  Anomaly detection on multivariate time-series is of great importance in both data mining research and industrial applications.
• Bandit Samplers for Training Graph Neural Networks
  10 Jun 2020 2 repositories listed Syntology ran 3 of 8 samples · 5 unverified
  However, due to the intractable computation of optimal sampling distribution, these sampling algorithms are suboptimal for GCNs and are not applicable to more general graph neural networks (GNNs) where the message…

Syntology lines on 11 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.