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Thomas Y. Chen
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2020 – today
- 2023
- [i7]Monica G. Bobra, Will T. Barnes, Thomas Y. Chen, Mark C. M. Cheung, Laura A. Hayes, Jack Ireland, Miho Janvier, Michael S. F. Kirk, James Mason, Stuart Mumford, Paul J. Wright:
Science Platforms for Heliophysics Data Analysis. CoRR abs/2301.00878 (2023) - 2022
- [c2]Thomas Y. Chen:
Multi-temporal deep learning-based social media analysis for disaster relief. MobiSys 2022: 585-586 - [i6]Thomas Y. Chen
:
Interpretability in Convolutional Neural Networks for Building Damage Classification in Satellite Imagery. CoRR abs/2201.10523 (2022) - [i5]Thomas Y. Chen
:
MonarchNet: Differentiating Monarch Butterflies from Butterflies Species with Similar Phenotypes. CoRR abs/2201.10526 (2022) - [i4]Thomas Y. Chen:
PreDefense: Defending Underserved AI Students and Researchers from Predatory Conferences. CoRR abs/2201.13268 (2022) - [i3]Gabriele Benelli, Thomas Y. Chen, Javier M. Duarte, Matthew Feickert, Matthew J. Graham, Lindsey Gray, Dan Hackett, Philip C. 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:
Data Science and Machine Learning in Education. CoRR abs/2207.09060 (2022) - [i2]Thomas Y. Chen, Biprateep Dey, Aishik Ghosh, Michael Kagan, Brian Nord
, Nesar Ramachandra:
Interpretable Uncertainty Quantification in AI for HEP. CoRR abs/2208.03284 (2022) - [i1]John C. Dorelli, Christopher M. Bard, Thomas Y. Chen, Daniel da Silva, Luiz Fernando Guides dos Santos, Jack Ireland, Michael Kirk, Ryan McGranaghan, Ayris Narock, Teresa Nieves-Chinchilla, Marilia Samara, Menelaos Sarantos, Pete Schuck, Barbara J. Thompson:
Deep Learning for Space Weather Prediction: Bridging the Gap between Heliophysics Data and Theory. CoRR abs/2212.13328 (2022) - 2021
- [c1]Thomas Y. Chen:
PreDefense: Defending Underserved AI Students and Researchers from Predatory Conferences. AIDBEI 2021: 1-6
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