Jesse Clifton

College of Sciences

Works (3)

Updated: August 5th, 2023 05:02

2023 article

Deep Spatial Q-Learning for Infectious Disease Control

Liu, Z., Clifton, J., Laber, E. B., Drake, J., & Fang, E. X. (2023, July 8). JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS.

By: Z. Liu*, J. Clifton n, E. Laber*, J. Drake * & E. Fang *

author keywords: Infectious diseases; Reinforcement learning; Graph neural networks
TL;DR: A novel model-free algorithm is developed for the online management of an infectious disease spreading over a finite set of locations and an indefinite or infinite time horizon and introduces a graph neural network-based estimator in order to improve the performance of this class of algorithms. (via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being (Web of Science; OpenAlex)
Source: Web Of Science
Added: July 31, 2023

2020 article

Q-Learning: Theory and Applications

ANNUAL REVIEW OF STATISTICS AND ITS APPLICATION, VOL 7, 2020, Vol. 7, pp. 279–301.

By: J. Clifton n & E. Laber n

author keywords: reinforcement learning; dynamic treatment regimes; model-free; causal inference; policy search
TL;DR: The history of Q-learning in computer science and statistics is reviewed, formalized within the potential outcomes framework, and variants of infinite-horizon Q- learning and the exploration-exploitation problem are reviewed, which arises in decision problems with a long time horizon. (via Semantic Scholar)
UN Sustainable Development Goal Categories
16. Peace, Justice and Strong Institutions (OpenAlex)
Source: Web Of Science
Added: March 23, 2020

2020 journal article

Use of standardized bioinformatics for the analysis of fungal DNA signatures applied to sample provenance

FORENSIC SCIENCE INTERNATIONAL, 310.

By: J. Allwood n, N. Fierer *, R. Dunn n , M. Breen n , B. Reich n , E. Laber n, J. Clifton n, N. Grantham n, S. Faith n

author keywords: Forensic microbiology; Bioinformatics; Metabarcoding; Sample provenance
MeSH headings : DNA Barcoding, Taxonomic; DNA, Fungal / chemistry; Demography; Forensic Sciences; Fungi; Humans; Reference Values; Soil
TL;DR: Investigating a small-scale approach as an adaptation of a larger metabarcoding study to develop a model for global sample provenance using fungal DNA signatures collected from dust swabs to facilitate a standardized method for consistent, reproducible sample treatment. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, NC State University Libraries
Added: May 26, 2020

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