92 citations · 237 across the 29 of their papers we have counts for
4 papers · 1 filter
Towards Seamless Management of AI Models in High-Performance Computing
Sixing Yu, Murali Emani, Chunhua Liao +4
With the increasing prevalence of artificial intelligence (AI) in diverse science/engineering communities, AI models emerge on an unprecedented scale among various domains. However…
Making Machine Learning Datasets and Models FAIR for HPC: A Methodology and Case Study
Pei-Hung Lin, Chunhua Liao, Winson Chen +3
The FAIR Guiding Principles aim to improve the findability, accessibility, interoperability, and reusability of digital content by making them both human and machine actionable. Ho…
FAIR for AI: An interdisciplinary and international community building perspective
E. A. Huerta, Ben Blaiszik, L. Catherine Brinson +21
A foundational set of findable, accessible, interoperable, and reusable (FAIR) principles were proposed in 2016 as prerequisites for proper data management and stewardship, with th…
Finding Reusable Machine Learning Components to Build Programming Language Processing Pipelines
Patrick Flynn, Tristan Vanderbruggen, Chunhua Liao +3
Programming Language Processing (PLP) using machine learning has made vast improvements in the past few years. Increasingly more people are interested in exploring this promising f…