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01/23/2023
DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion
Real-world data generation often involves complex inter-dependencies amo...
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09/01/2022
MSGNN: A Spectral Graph Neural Network Based on a Novel Magnetic Signed Laplacian
Signed and directed networks are ubiquitous in real-world applications. ...
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05/21/2022
CEP3: Community Event Prediction with Neural Point Process on Graph
Many real world applications can be formulated as event forecasting on C...
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02/22/2022
PyTorch Geometric Signed Directed: A Survey and Software on Graph Neural Networks for Signed and Directed Graphs
Signed networks are ubiquitous in many real-world applications (e.g., so...
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02/01/2022
GNNRank: Learning Global Rankings from Pairwise Comparisons via Directed Graph Neural Networks
Recovering global rankings from pairwise comparisons is an important pro...
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10/13/2021
SSSNET: Semi-Supervised Signed Network Clustering
Node embeddings are a powerful tool in the analysis of networks; yet, th...
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06/09/2021
DIGRAC: Digraph Clustering with Flow Imbalance
Node clustering is a powerful tool in the analysis of networks. Here, we...
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04/15/2021
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models
We present PyTorch Geometric Temporal a deep learning framework combinin...
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06/08/2019