1 citations · 1 across the 2 of their papers we have counts for
3 papers
Towards Practical Explainability with Cluster Descriptors
Xiaoyuan Liu, Ilya Tyagin, Hayato Ushijima-Mwesigwa +2
With the rapid development of machine learning, improving its explainability has become a crucial research goal. We study the problem of making the clusters more explainable by inv…
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…
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…