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Topological Data Analysis and Neural Networks

Reduction of Large-Scale Scientific Data with Topological Data Analysis and Neural Networks

Our computational science capabilities have created a recent explosion of data that is rapidly changing how the scientific community investigates complex phenomenon. In particular, we are now leveraging high performance computing resources to simulate across a variety of applications of interest.The challenges of analyzing scientific data are particularly severe because they are large and unwieldy.

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fact fake

uSing argUmentation foR Fact-checkING (SURFING)

Some grand challenges facing humanity include climate change and health. Unfortunately, implementing effective solutions for these challenges is counteracted by misinformation, disinformation, and malinformation (MDM), e.g., climate change denying or anti-vaccine propaganda. To address this issue, we propose robust and holistic fact verification methods. The proposed methods can reduce data bias, aggregate information across multiple statements, and yield global conclusions.

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France-Arizona Institute for Global Grand Challenges | Home

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