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Displaying 76 - 100 of 433

Characterization of AI Model Configurations For Model Reuse

October 24, 2022
Author(s)
Peter Bajcsy, Daniel Gao, Michael Paul Majurski, Thomas Cleveland, Manuel Carrasco, Michael Buschmann, Walid Keyrouz
With the widespread creation of artificial intelligence (AI) models in biosciences, bio-medical researchers are reusing trained AI models from other applications. This work is motivated by the need to characterize trained AI models for reuse based on

Glycosylation and the global virome

October 10, 2022
Author(s)
Cassandra Pegg, Benjamin Schulz, Ben Neely, Gregory Albery, Colin Carlson
The sugars that coat the outsides of viruses and host cells are key to successful disease transmission, but they remain understudied compared to other molecular features. Understanding the comparative zoology of glycosylation - and harnessing it for

Towards Generative Adversarial Network on Industrial Internet of Things

October 1, 2022
Author(s)
Cheng Qian, Wei Yu, Chao Lu, David W. Griffith, Nada T. Golmie
Machine learning, as a viable way of conducting data analytics, has been successfully applied to a number of areas. Nonetheless, the lack of sufficient data is one critical issue for applying machine learning in Industrial Internet of Things (IIoT) systems

The Industrial Ontologies Foundry (IOF) Core Ontology

September 19, 2022
Author(s)
Boonserm Kulvatunyou, Milos Drobnjakovic, Farhad Ameri, Chris Will, Barry Smith
The Industrial Ontologies Foundry (IOF) has been formed to create a suite of interoperable ontologies that would serve as a foundation for data and information interoperability in all areas of manufacturing. To ensure that the ontologies are developed in a

Leveraging Theory for Enhanced Machine Learning

August 26, 2022
Author(s)
Debra Audus, Austin McDannald, Brian DeCost
The application of machine learning to the materials domain has traditionally struggled with two major challenges: a lack of large, curated data sets and the need to understand the physics behind the machine-learning prediction. The former problem is

NIST Explainable AI Workshop Summary

August 25, 2022
Author(s)
P. Jonathon Phillips, Carina Hahn, Peter Fontana, Amy Yates, Matthew Smith
This report represents a summary of the National Institute of Standards and Technology (NIST) Explainable Artificial Intelligence (AI) Workshop, which NIST held virtually on January 26-28, 2021.
Displaying 76 - 100 of 433