Search Results for author: Thomas Y. Chen

Found 5 papers, 0 papers with code

Interpretable Uncertainty Quantification in AI for HEP

no code implementations5 Aug 2022 Thomas Y. Chen, Biprateep Dey, Aishik Ghosh, Michael Kagan, Brian Nord, Nesar Ramachandra

Estimating uncertainty is at the core of performing scientific measurements in HEP: a measurement is not useful without an estimate of its uncertainty.

Decision Making Uncertainty Quantification

Data Science and Machine Learning in Education

no code implementations19 Jul 2022 Gabriele Benelli, Thomas Y. Chen, Javier Duarte, Matthew Feickert, Matthew Graham, Lindsey Gray, Dan Hackett, Phil Harris, Shih-Chieh Hsu, Gregor Kasieczka, Elham E. Khoda, Matthias Komm, Mia Liu, Mark S. Neubauer, Scarlet Norberg, Alexx Perloff, Marcel Rieger, Claire Savard, Kazuhiro Terao, Savannah Thais, Avik Roy, Jean-Roch Vlimant, Grigorios Chachamis

The growing role of data science (DS) and machine learning (ML) in high-energy physics (HEP) is well established and pertinent given the complex detectors, large data, sets and sophisticated analyses at the heart of HEP research.

BIG-bench Machine Learning

MonarchNet: Differentiating Monarch Butterflies from Butterflies Species with Similar Phenotypes

no code implementations24 Jan 2022 Thomas Y. Chen

We seek to contribute to the study of biodiversity and butterfly ecology by providing a novel method for computational classification of these particular butterfly species.

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