Braid-DB: Toward AI-Driven Science with Machine Learning Provenance

Author:

Wozniak Justin M.,Liu Zhengchun,Vescovi Rafael,Chard Ryan,Nicolae Bogdan,Foster Ian

Publisher

Springer International Publishing

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. DLProv: A Data-Centric Support for Deep Learning Workflow Analyses;Proceedings of the Eighth Workshop on Data Management for End-to-End Machine Learning;2024-06-09

2. PINNProv: Provenance for Physics-Informed Neural Networks;2023 International Symposium on Computer Architecture and High Performance Computing Workshops (SBAC-PADW);2023-10-17

3. Building the I (Interoperability) of FAIR for Performance Reproducibility of Large-Scale Composable Workflows in RECUP;2023 IEEE 19th International Conference on e-Science (e-Science);2023-10-09

4. Tracking Dubious Data: Protecting Scientific Workflows from Invalidated Experiments;2022 IEEE 18th International Conference on e-Science (e-Science);2022-10

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