activity
20202022
most citedThe Shapley Value in Machine Learning

17 citations · 26 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG202217 cited

The Shapley Value in Machine Learning

Benedek Rozemberczki, Lauren Watson, Péter Bayer +4

Over the last few years, the Shapley value, a solution concept from cooperative game theory, has found numerous applications in machine learning. In this paper, we first discuss fu…

cs.LG2021

PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models

Benedek Rozemberczki, Paul Scherer, Yixuan He +8

We present PyTorch Geometric Temporal a deep learning framework combining state-of-the-art machine learning algorithms for neural spatiotemporal signal processing. The main goal of…

cs.LG20217 cited

Chickenpox Cases in Hungary: a Benchmark Dataset for Spatiotemporal Signal Processing with Graph Neural Networks

Benedek Rozemberczki, Paul Scherer, Oliver Kiss +2

Recurrent graph convolutional neural networks are highly effective machine learning techniques for spatiotemporal signal processing. Newly proposed graph neural network architectur…

cs.SI20202 cited

Little Ball of Fur: A Python Library for Graph Sampling

Benedek Rozemberczki, Oliver Kiss, Rik Sarkar

Sampling graphs is an important task in data mining. In this paper, we describe Little Ball of Fur a Python library that includes more than twenty graph sampling algorithms. Our go…

cs.LG2020

Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs

Benedek Rozemberczki, Oliver Kiss, Rik Sarkar

We present Karate Club a Python framework combining more than 30 state-of-the-art graph mining algorithms which can solve unsupervised machine learning tasks. The primary goal of t…