Practicum 1: Paper Replication and Reproducible Research Workflow
A first research experience: reproducing a scientific paper from start to finish
MF
Mikhail Fadin
About the course
Students select a real ML paper (NeurIPS/ICML/ICLR-tier) and reproduce its results within a reproducible workflow. The practicum builds skills in critical reading of the literature, experiment organization, and presenting code as a research artifact. The deliverable is a public repository with a notebook, a report on deviations, and a reflection on the original methodology.
What you'll learn
✓Reproduce the core results of a published ML paper with documented discrepancies
✓Organize a project to reproducible-research standards (environment, versioning, seed management)
✓Write a technical report analyzing the original authors' methodological choices
Key topics
•Critical reading of ML papers: the anatomy of a Methods section
•Reproducible workflow: seeds, environments, data versioning