3 citations · 6 across the 8 of their papers we have counts for
8 papers
Q3SAT-GPT: A Generative Model for Discovering Quantum Circuits for the 3-SAT Problem
Pratim Ugale, Ilya Tyagin, Karunya Shirali +2
This work introduces Q3SAT-GPT, a generative model for discovering quantum circuits for the Max-E3-SAT problem. Our method learns from high-performing QAOA-style ansätze to directl…
Biomedical Hypothesis Explainability with Graph-Based Context Retrieval
Ilya Tyagin, Saeideh Valipour, Aliaksandra Sikirzhytskaya +2
We introduce an explainability method for biomedical hypothesis generation systems, built on top of the novel Hypothesis Generation Context Retriever framework. Our approach combin…
QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits
Ilya Tyagin, Marwa H. Farag, Kyle Sherbert +3
Quantum computing has the potential to improve our ability to solve certain optimization problems that are computationally difficult for classical computers, by offering new algori…
Dyport: Dynamic Importance-based Hypothesis Generation Benchmarking Technique
Ilya Tyagin, Ilya Safro
This paper presents a novel benchmarking framework Dyport for evaluating biomedical hypothesis generation systems. Utilizing curated datasets, our approach tests these systems unde…
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…
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…