17 citations · 54 across the 12 of their papers we have counts for
19 papers · 1 filter
TigerLily: Finding drug interactions in silico with the Graph
Benedek Rozemberczki
Tigerlily is a TigerGraph based system designed to solve the drug interaction prediction task. In this machine learning task, we want to predict whether two drugs have an adverse i…
Synthetic Graph Generation to Benchmark Graph Learning
Anton Tsitsulin, Benedek Rozemberczki, John Palowitch +1
Graph learning algorithms have attained state-of-the-art performance on many graph analysis tasks such as node classification, link prediction, and clustering. It has, however, bec…
Continual and Sliding Window Release for Private Empirical Risk Minimization
Lauren Watson, Abhirup Ghosh, Benedek Rozemberczki +1
It is difficult to continually update private machine learning models with new data while maintaining privacy. Data incur increasing privacy loss -- as measured by differential pri…
PyTorch Geometric Signed Directed: A Software Package on Graph Neural Networks for Signed and Directed Graphs
Yixuan He, Xitong Zhang, Junjie Huang +3
Networks are ubiquitous in many real-world applications (e.g., social networks encoding trust/distrust relationships, correlation networks arising from time series data). While man…
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…
ChemicalX: A Deep Learning Library for Drug Pair Scoring
Benedek Rozemberczki, Charles Tapley Hoyt, Anna Gogleva +9
In this paper, we introduce ChemicalX, a PyTorch-based deep learning library designed for providing a range of state of the art models to solve the drug pair scoring task. The prim…