Benedek Rozemberczki | DeepAI

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∙ 06/05/2022

OntoMerger: An Ontology Integration Library for Deduplicating and Connecting Knowledge Graph Nodes

Duplication of nodes is a common problem encountered when building knowl...

4 David Geleta, et al. ∙

∙ 04/18/2022

TigerLily: Finding drug interactions in silico with the Graph

Tigerlily is a TigerGraph based system designed to solve the drug intera...

0 Benedek Rozemberczki, et al. ∙

∙ 04/04/2022

Synthetic Graph Generation to Benchmark Graph Learning

Graph learning algorithms have attained state-of-the-art performance on ...

0 Anton Tsitsulin, et al. ∙

∙ 03/07/2022

Continual and Sliding Window Release for Private Empirical Risk Minimization

It is difficult to continually update private machine learning models wi...

4 Lauren Watson, et al. ∙

∙ 02/11/2022

The Shapley Value in Machine Learning

Over the last few years, the Shapley value, a solution concept from coop...

1 Benedek Rozemberczki, et al. ∙

∙ 11/20/2021

Explainable Biomedical Recommendations via Reinforcement Learning Reasoning on Knowledge Graphs

For Artificial Intelligence to have a greater impact in biology and medi...

0 Gavin Edwards, et al. ∙

∙ 11/04/2021

A Unified View of Relational Deep Learning for Polypharmacy Side Effect, Combination Synergy, and Drug-Drug Interaction Prediction

In recent years, numerous machine learning models which attempt to solve...

0 Benedek Rozemberczki, et al. ∙

∙ 10/28/2021

MOOMIN: Deep Molecular Omics Network for Anti-Cancer Drug Combination Therapy

We propose the molecular omics network (MOOMIN) a multimodal graph neura...

0 Benedek Rozemberczki, et al. ∙

∙ 04/15/2021

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

We present PyTorch Geometric Temporal a deep learning framework combinin...

0 Benedek Rozemberczki, et al. ∙

∙ 02/16/2021

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

Recurrent graph convolutional neural networks are highly effective machi...

0 Benedek Rozemberczki, et al. ∙

∙ 01/08/2021

Twitch Gamers: a Dataset for Evaluating Proximity Preserving and Structural Role-based Node Embeddings

Proximity preserving and structural role-based node embeddings became a ...

0 Benedek Rozemberczki, et al. ∙

∙ 01/06/2021

The Shapley Value of Classifiers in Ensemble Games

How do we decide the fair value of individual classifiers in an ensemble...

0 Benedek Rozemberczki, et al. ∙

∙ 10/24/2020

Pathfinder Discovery Networks for Neural Message Passing

In this work we propose Pathfinder Discovery Networks (PDNs), a method f...

0 Benedek Rozemberczki, et al. ∙

∙ 07/03/2020

Scaling Graph Neural Networks with Approximate PageRank

Graph neural networks (GNNs) have emerged as a powerful approach for sol...

0 Aleksandar Bojchevski, et al. ∙

∙ 06/25/2020

Stability Enhanced Privacy and Applications in Private Stochastic Gradient Descent

Private machine learning involves addition of noise while training, resu...

2 Lauren Watson, et al. ∙

∙ 06/08/2020

Little Ball of Fur: A Python Library for Graph Sampling

Sampling graphs is an important task in data mining. In this paper, we d...

0 Benedek Rozemberczki, et al. ∙

∙ 05/16/2020

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 ...

0 Benedek Rozemberczki, et al. ∙

∙ 03/10/2020

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...

0 Benedek Rozemberczki, et al. ∙

∙ 01/21/2020

Fast Sequence-Based Embedding with Diffusion Graphs

A graph embedding is a representation of graph vertices in a low-dimensi...

0 Benedek Rozemberczki, et al. ∙

∙ 09/28/2019

Multi-scale Attributed Node Embedding

We present network embedding algorithms that capture information about a...

0 Benedek Rozemberczki, et al. ∙

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