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PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models
We present PyTorch Geometric Temporal a deep learning framework combinin...
04/15/2021 ∙ by Benedek Rozemberczki, et al. ∙
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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...
02/16/2021 ∙ by Benedek Rozemberczki, et al. ∙
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Twitch Gamers: a Dataset for Evaluating Proximity Preserving and Structural Role-based Node Embeddings
Proximity preserving and structural role-based node embeddings became a ...
01/08/2021 ∙ by Benedek Rozemberczki, et al. ∙
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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...
01/06/2021 ∙ by Benedek Rozemberczki, et al. ∙
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Pathfinder Discovery Networks for Neural Message Passing
In this work we propose Pathfinder Discovery Networks (PDNs), a method f...
10/24/2020 ∙ by Benedek Rozemberczki, et al. ∙
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Scaling Graph Neural Networks with Approximate PageRank
Graph neural networks (GNNs) have emerged as a powerful approach for sol...
07/03/2020 ∙ by Aleksandar Bojchevski, et al. ∙
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Stability Enhanced Privacy and Applications in Private Stochastic Gradient Descent
Private machine learning involves addition of noise while training, resu...
06/25/2020 ∙ by Lauren Watson, et al. ∙
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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...
06/08/2020 ∙ by Benedek Rozemberczki, et al. ∙
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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 ...
05/16/2020 ∙ by Benedek Rozemberczki, et al. ∙
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An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs
We present Karate Club a Python framework combining more than 30 state-o...
03/10/2020 ∙ by Benedek Rozemberczki, et al. ∙
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Karate Club a Python library for graph representation learning
03/08/2020 ∙ Benedek Rozemberczki ∙
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Fast Sequence-Based Embedding with Diffusion Graphs
A graph embedding is a representation of graph vertices in a low-dimensi...
01/21/2020 ∙ by Benedek Rozemberczki, et al. ∙
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Multi-scale Attributed Node Embedding
We present network embedding algorithms that capture information about a...
09/28/2019 ∙ by Benedek Rozemberczki, et al. ∙
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