A Low Overhead Approach for Automatically Tracking Provenance in Machine Learning Workflows
Author:
Affiliation:
1. Institute of Software Methods for Product Virtualiration (SP), German Aerospace Center (DLR),Dresden,Germany
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10628447/10628451/10628755.pdf?arnumber=10628755
Reference20 articles.
1. An Overview of Hybrid RANS-LES Models Developed for Industrial CFD;Menter;Applied Sciences,2021
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3. Load Balancing for Immersed Boundaries in Coupled Simulations
4. Application of artificial neural network for understanding multi-layer micro scale transport comprising of alternate newtonian and non-newtonian fluids,”;Shubhangee;Colloids and Surfaces A: Physicochemical and Engineering Aspects,2022
5. Predicting Performance of Briquette Made from Millet Bran: ANeural Network Approach;Kumar;Advanced Journal of Graduate Research,2020
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