Notice
Session 1: Provenance and Reproducibility
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Descriptif
Talk 1 [00:00] : Computational Experiment Comprehension Using Provenance Summarization. By Nichole Boufford, Joseph Wonsil, Adam Pocock, Jack Sullivan, Margo Seltzer and Thomas Pasquier (Best Paper Finalist)
Presented by Nichole Bouffordl, PhD Student.
Talk 2 [23:43] : A Benchmark Suite And Performance Analysis Of User-Space Provenance Collectors. By Samuel Grayson, Faustino Aguilar, Reed Milewicz, Daniel S. Katz and Darko Marinov
Presented by Samuel Grayson, PhD Student.
Thème
Sur le même thème
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Tutorial Track 1: Reproducible distributed environments with NixOS Compose
Presented by Quentin Guilloteau, Postdoctoral Fellow, Fernando Ayats Llamas, Research Engineer and Olivier Richard, Assistant Professor.
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Tutorial Track 1: Reproducibility of Scientific Results using E4S Containers
Presented by SHENDE, Sameer, Research Profesor.
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Tutorial Track2: Fostering Reproducibility By Integrating Large Language Model and Scholarly Knowl…
Presented by Hassan Hussein, PhD Student, Vindoh Ilangovan, Researcher and Kaouter Kebaili, PhD Student.
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Tutorial Track 3: Managing HPC Software Complexity with Spack
Presented by Massimiliano Culpo, Researcher.
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Tutorial Track 4: Practical strategies for teaching reproducibility
Presented by Fraida Fund, Research Assistant Professor, Sarah Cohen-Boulakia, Professor and Bogdan Alexandru Stoica, PhD Student.
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Keynote: Replicable empirical machine learning research
BoulesteixAnne-LaureIn the absence of mathematical theory addressing complex real-life settings beyond simplifying assumptions, the behavior and performance of machine learning methods often has to be addressed by
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Session 4: Poster Lightning Talks
Talk 1 [00:00] NPF: orchestrate and reproduce network experiments. By Tom Barbette. Presented by Tom Barbette, Assistant Professor. Talk 2 [03:10] : From reproducible to reusable bioinformatics
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Keynote: Reproducibility and replicability of computer simulations
HinsenKonradSince the early days of the reproducibility crisis, much progress has been made in understanding and improving computational reproducibility and replicability (R&R). What have we accomplished so far,
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