
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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Chickenpox Cases in Hungary: a Benchmark Dataset for Spatiotemporal Signal Processing with Graph Neural Networks
Recurrent graph convolutional neural networks are highly effective machi...
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Twitch Gamers: a Dataset for Evaluating Proximity Preserving and Structural Rolebased Node Embeddings
Proximity preserving and structural rolebased node embeddings became a ...
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The Shapley Value of Classifiers in Ensemble Games
How do we decide the fair value of individual classifiers in an ensemble...
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Pathfinder Discovery Networks for Neural Message Passing
In this work we propose Pathfinder Discovery Networks (PDNs), a method f...
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Scaling Graph Neural Networks with Approximate PageRank
Graph neural networks (GNNs) have emerged as a powerful approach for sol...
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Stability Enhanced Privacy and Applications in Private Stochastic Gradient Descent
Private machine learning involves addition of noise while training, resu...
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Little Ball of Fur: A Python Library for Graph Sampling
Sampling graphs is an important task in data mining. In this paper, we d...
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Characteristic Functions on Graphs: Birds of a Feather, from Statistical Descriptors to Parametric Models
In this paper, we propose a flexible notion of characteristic functions ...
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An API Oriented Opensource Python Framework for Unsupervised Learning on Graphs
We present Karate Club a Python framework combining more than 30 stateo...
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Fast SequenceBased Embedding with Diffusion Graphs
A graph embedding is a representation of graph vertices in a lowdimensi...
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Multiscale Attributed Node Embedding
We present network embedding algorithms that capture information about a...
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Benedek Rozemberczki
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