Perspectives on Machine Learning from Psychology's Reproducibility Crisis

18 April 2021

Papers citing "Perspectives on Machine Learning from Psychology's Reproducibility Crisis"

7 / 7 papers shown

Title
Sensitivity-Aware Amortized Bayesian Inference Lasse Elsemüller Hans Olischläger Marvin Schmitt Paul-Christian Bürkner Ullrich Kothe Stefan T. Radev 33 7 0 17 Oct 2023
REFORMS: Reporting Standards for Machine Learning Based Science Sayash Kapoor Emily F. Cantrell Kenny Peng Thanh Hien Pham C. Bail ... Matthew J. Salganik Marta Serra-Garcia Brandon M Stewart Gilles Vandewiele Arvind Narayanan 10 19 0 15 Aug 2023
Leakage and the Reproducibility Crisis in ML-based Science Sayash Kapoor Arvind Narayanan 25 177 0 14 Jul 2022
Modeling the Machine Learning Multiverse Samuel J. Bell Onno P. Kampman Jesse Dodge Neil D. Lawrence 26 17 0 13 Jun 2022
Prescriptive and Descriptive Approaches to Machine-Learning Transparency David Adkins B. Alsallakh Adeel Cheema Narine Kokhlikyan Emily McReynolds Pushkar Mishra Chavez Procope Jeremy Sawruk Erin Wang Polina Zvyagina 8 13 0 27 Apr 2022
The worst of both worlds: A comparative analysis of errors in learning from data in psychology and machine learning Jessica Hullman Sayash Kapoor Priyanka Nanayakkara Andrew Gelman Arvind Narayanan 33 39 0 12 Mar 2022
Behavioral Experiments for Understanding Catastrophic Forgetting Samuel J. Bell Neil D. Lawrence 35 4 0 20 Oct 2021