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20192023
most citedWorkflow Provenance in the Lifecycle of Scientific Machine Learning

44 citations · 62 across the 9 of their papers we have counts for

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6 papers · 1 filter

cs.DC2023★ 1 cited

Towards Lightweight Data Integration using Multi-workflow Provenance and Data Observability

Renan Souza, Tyler J. Skluzacek, Sean R. Wilkinson +2

Modern large-scale scientific discovery requires multidisciplinary collaboration across diverse computing facilities, including High Performance Computing (HPC) machines and the Ed…

cs.DC2023

Workflows Community Summit 2022: A Roadmap Revolution

Rafael Ferreira da Silva, Rosa M. Badia, Venkat Bala +102

Scientific workflows have become integral tools in broad scientific computing use cases. Science discovery is increasingly dependent on workflows to orchestrate large and complex s…

cs.DC2021

Context-aware Execution Migration Tool for Data Science Jupyter Notebooks on Hybrid Clouds

Renato L. F. Cunha, Lucas V. Real, Renan Souza +2

Interactive computing notebooks, such as Jupyter notebooks, have become a popular tool for developing and improving data-driven models. Such notebooks tend to be executed either in…

cs.DC2021

Workflows Community Summit: Advancing the State-of-the-art of Scientific Workflows Management Systems Research and Development

Rafael Ferreira da Silva, Henri Casanova, Kyle Chard +55

Scientific workflows are a cornerstone of modern scientific computing, and they have underpinned some of the most significant discoveries of the last decade. Many of these workflow…

cs.DC2021★ 4 cited

Distributed In-memory Data Management for Workflow Executions

Renan Souza, Vítor Silva, Alexandre A. B. Lima +3

Complex scientific experiments from various domains are typically modeled as workflows and executed on large-scale machines using a Parallel Workflow Management System (WMS). Since…

cs.DC2019

Provenance Data in the Machine Learning Lifecycle in Computational Science and Engineering

Renan Souza, Leonardo Azevedo, Vítor Lourenço +10

Machine Learning (ML) has become essential in several industries. In Computational Science and Engineering (CSE), the complexity of the ML lifecycle comes from the large variety of…