1 citations · 1 across the 3 of their papers we have counts for
9 papers
Literature-based Discovery for Landscape Planning
David Marasco, Ilya Tyagin, Justin Sybrandt +2
This project demonstrates how medical corpus hypothesis generation, a knowledge discovery field of AI, can be used to derive new research angles for landscape and urban planners. T…
SmartChoices: Augmenting Software with Learned Implementations
Daniel Golovin, Gabor Bartok, Eric Chen +7
In many software systems, heuristics are used to make decisions - such as cache eviction, task scheduling, and information presentation - that have a significant impact on overall…
Accelerating COVID-19 research with graph mining and transformer-based learning
Ilya Tyagin, Ankit Kulshrestha, Justin Sybrandt +3
In 2020, the White House released the, "Call to Action to the Tech Community on New Machine Readable COVID-19 Dataset," wherein artificial intelligence experts are asked to collect…
Accelerating Text Mining Using Domain-Specific Stop Word Lists
Farah Alshanik, Amy Apon, Alexander Herzog +2
Text preprocessing is an essential step in text mining. Removing words that can negatively impact the quality of prediction algorithms or are not informative enough is a crucial st…
Unsupervised Hierarchical Graph Representation Learning by Mutual Information Maximization
Fei Ding, Xiaohong Zhang, Justin Sybrandt +1
Graph representation learning based on graph neural networks (GNNs) can greatly improve the performance of downstream tasks, such as node and graph classification. However, the gen…
AGATHA: Automatic Graph-mining And Transformer based Hypothesis generation Approach
Justin Sybrandt, Ilya Tyagin, Michael Shtutman +1
Medical research is risky and expensive. Drug discovery, as an example, requires that researchers efficiently winnow thousands of potential targets to a small candidate set for mor…