activity
20222025
most citedSources of Irreproducibility in Machine Learning: A Review

33 citations · 67 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CY2025

Now More Than Ever, Foundational AI Research and Infrastructure Depends on the Federal Government

Michela Taufer, Rada Mihalcea, Matthew Turk +13

Leadership in the field of AI is vital for our nation's economy and security. Maintaining this leadership requires investments by the federal government. The federal investment in…

cs.AI2025★ 2 cited

AI Copilots for Reproducibility in Science: A Case Study

Adrien Bibal, Steven N. Minton, Deborah Khider +1

Open science initiatives seek to make research outputs more transparent, accessible, and reusable, but ensuring that published findings can be independently reproduced remains a pe…

cs.AI2025★ 32 cited

Artificial Intelligence Index Report 2025

Nestor Maslej, Loredana Fattorini, Raymond Perrault +20

Welcome to the eighth edition of the AI Index report. The 2025 Index is our most comprehensive to date and arrives at an important moment, as AI's influence across society, the eco…

cs.AI2024

Envisioning National Resources for Artificial Intelligence Research: NSF Workshop Report

Shantenu Jha, Yolanda Gil

This is a report of an NSF workshop titled "Envisioning National Resources for Artificial Intelligence Research" held in Alexandria, Virginia, in May 2024. The workshop aimed to id…

cs.LG2022★ 33 cited

Sources of Irreproducibility in Machine Learning: A Review

Odd Erik Gundersen, Kevin Coakley, Christine Kirkpatrick +1

Background: Many published machine learning studies are irreproducible. Issues with methodology and not properly accounting for variation introduced by the algorithm themselves or…