Download BibTex Recent years have witnessed the emerging success of graph neural networks (GNNs) for modeling structured data. However, most GNNs are designed for homogeneous graphs, in which all nodes and edges belong to the same types, making them infeasible to represent heterogeneous structures....
SPIGA: Shape Preserving Facial Landmarks with Graph Attention Networks. This repository contains the source code of SPIGA, a face alignment and headpose estimator that takes advantage of the complementary benefits from CNN and GNN architectures producing plausible face shapes in presence of strong appe...
which simultaneously model users' dynamic interests and context-dependent social influences. First, we model users' dynamic interests with recurrent neural networks. In order to model context-dependent social influences, we propose to employ attention-based graph convolutional neural networks to differentiat...
including the large and challenging CLRS Algorithmic Reasoning Benchmark. There, it dramatically outperforms state-of-the-art graph neural networks expressly designed to reason over graph-structured data. Our analysis demonstrates that these gains are attributable to relational at...
With the recent advances in information networks, the problem of identifying group structure or communities has received a significant amount of attention. Most of the existing principles of community detection or clustering mainly focus on either the topological structure of a network or the node attr...
DGFraudis a Graph Neural Network (GNN) based toolbox for fraud detection. It integrates the implementation & comparison of state-of-the-art GNN-based fraud detection models. The introduction of implemented models can be foundhere. We welcome contributions on adding new fraud detectors and extending...
BibTeX @inproceedings{ kim2021how, title={How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision}, author={Dongkwan Kim and Alice Oh}, booktitle={International Conference on Learning Representations}, year={2021}, url={https://openreview.net/forum?id=Wi5KUNlqWty}...
so I probably will not see your emails for several weeks, potentially longer. Also, I have a job that I love and that pays my bills, and thus takes priority. That being said, the blue little notification dot on GitHub is surprisingly effective at getting my attention. So please just rais...
VDN: Value-Decomposition Networks For Cooperative Multi-Agent Learning IQL: Independent Q-Learning G2ANet: Multi-Agent Game Abstraction via Graph Attention Neural Network QTRAN: QTRAN: Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning ...
(SGT) where we use node embedding to leverage the self-attention mechanism to ensure that the information flow between two sensors is adaptive with respect to the unique dynamic of each pair. Finally, we present Graph Self-attention WaveNet (G-SWaN) to address the complex, non-linear spatio...