Notice
Session 5: Reproducibility Enhancing Frameworks
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Descriptif
Talk 1 [00:00] : Reproscreener: Leveraging LLMs For Assessing Computational Reproducibility Of Machine Learning Pipelines. By Adhithya Bhaskar and Victoria Stodden.
Presented by Adhithya Bhaskar, PhD Student.
Talk 2 [22:13] : MLXP: A Framework For Conducting Replicable Machine Learning Experiments In Python. By Michael Arbel and Alexander Zouaoui.
Presented by Michael Arbel, Researcher.
Talk 3 [48:23] : LogFlux: A Software Suite For Replicating Results In Automated Log Parsing. By Guineng Zheng, Robert Ricci and Vivek Srikumar.
Presented by Robert Ricci, Associate Professor.
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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