Graphs@SEI Collection
These publications describe Graphs@SEI, which provides a complete understanding of a system's behavior, effectiveness, vulnerability, and safety.
Publisher:
Software Engineering Institute
Abstract
Graphs are everywhere. They’re in computer networks, social connections, web traffic, sensor recordings, manufacturing workflows, supply chains, natural languages, molecules, maps. They’re anywhere when relationship and position are important. Graphs@SEI combines the SEI’s graph processing and AI engineering expertise with its expertise in developing analysis techniques and tools. This multifaceted work pushes the boundaries of graph analysis to reveal otherwise hidden patterns in data, providing a more complete understanding of a system’s behavior, effectiveness, vulnerability, and safety.
Collection Contents
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2019 SEI Year in Review
June 17, 2020 • Annual Report
The 2019 SEI Year in Review highlights the work of the institute undertaken during the fiscal year spanning October 1, 2018, to September 30, 2019.
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CMU SEI Research Review 2019 Project Descriptions and Posters
November 1, 2019 • Annual Report
By Thomas A. Longstaff
This brochure includes descriptive information about the SEI's fiscal year 2019 research portfolio
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GraphBLAS Forum Collection
July 23, 2020 • Collection
These publications describe Graphs@SEI, which encompasses SEI's research into graph processing and related areas of AI engineering.
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Spiral AI/ML Collection
July 22, 2020 • Collection
These publications describe a hardware/software co-optimization system that picks hardware configurations and generates optimized code.
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Graph Convolutional Neural Networks (GCNN) Collection
July 22, 2020 • Collection
These publications describe the SEI's applied graph signal processing techniques that create new tools for GCNNs.
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