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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...
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04/18/2022
TigerLily: Finding drug interactions in silico with the Graph
Tigerlily is a TigerGraph based system designed to solve the drug intera...
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04/04/2022
Synthetic Graph Generation to Benchmark Graph Learning
Graph learning algorithms have attained state-of-the-art performance on ...
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03/07/2022
Continual and Sliding Window Release for Private Empirical Risk Minimization
It is difficult to continually update private machine learning models wi...
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02/11/2022
The Shapley Value in Machine Learning
Over the last few years, the Shapley value, a solution concept from coop...
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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...
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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...
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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...
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04/15/2021
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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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...
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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 ...
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01/06/2021
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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10/24/2020
Pathfinder Discovery Networks for Neural Message Passing
In this work we propose Pathfinder Discovery Networks (PDNs), a method f...
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07/03/2020
Scaling Graph Neural Networks with Approximate PageRank
Graph neural networks (GNNs) have emerged as a powerful approach for sol...
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06/25/2020
Stability Enhanced Privacy and Applications in Private Stochastic Gradient Descent
Private machine learning involves addition of noise while training, resu...
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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...
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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 ...
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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...
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01/21/2020
Fast Sequence-Based Embedding with Diffusion Graphs
A graph embedding is a representation of graph vertices in a low-dimensi...
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09/28/2019