Savannah Thais

According to our database1, Savannah Thais authored at least 20 papers between 2018 and 2023.

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Bibliography

2023
Equivariance Is Not All You Need: Characterizing the Utility of Equivariant Graph Neural Networks for Particle Physics Tasks.
CoRR, 2023

AI and the EU Digital Markets Act: Addressing the Risks of Bigness in Generative AI.
CoRR, 2023

Equivariant Graph Neural Networks for Charged Particle Tracking.
CoRR, 2023

2022
Graph Neural Networks for Charged Particle Tracking on FPGAs.
Frontiers Big Data, 2022

Applications and Techniques for Fast Machine Learning in Science.
Frontiers Big Data, 2022

Data Science and Machine Learning in Education.
CoRR, 2022

Graph Neural Networks in Particle Physics: Implementations, Innovations, and Challenges.
CoRR, 2022

Symmetry Group Equivariant Architectures for Physics.
CoRR, 2022

Semi-Equivariant GNN Architectures for Jet Tagging.
CoRR, 2022

Understanding Historical, Socio-Economic, and Policy Contributions to COVID-19 Health Inequities.
Proceedings of the 19th International Conference on Information Systems for Crisis Response and Management, 2022

2021
Software Training in HEP.
Comput. Softw. Big Sci., 2021

Charged Particle Tracking via Edge-Classifying Interaction Networks.
Comput. Softw. Big Sci., 2021

Graph Neural Networks for Charged Particle Tracking on FPGAs.
CoRR, 2021

Applications and Techniques for Fast Machine Learning in Science.
CoRR, 2021

Physics and Computing Performance of the Exa.TrkX TrackML Pipeline.
CoRR, 2021

Instance Segmentation GNNs for One-Shot Conformal Tracking at the LHC.
CoRR, 2021

Correction to: Towards intellectual freedom in an AI Ethics Global Community.
AI Ethics, 2021

Towards intellectual freedom in an AI Ethics Global Community.
AI Ethics, 2021

2020
Accelerated Charged Particle Tracking with Graph Neural Networks on FPGAs.
CoRR, 2020

2018
Machine Learning in High Energy Physics Community White Paper.
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CoRR, 2018


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