Towards CRISP-ML(Q): A Machine Learning Process Model with Quality
Assurance Methodology

Towards CRISP-ML(Q): A Machine Learning Process Model with Quality Assurance Methodology

11 March 2020

Klaus-Robert Muller

Papers citing "Towards CRISP-ML(Q): A Machine Learning Process Model with Quality Assurance Methodology"

12 / 12 papers shown

Title
Offensive Security for AI Systems: Concepts, Practices, and Applications Josh Harguess Chris M. Ward AAML 21 0 0 09 May 2025
Machine Learning with Requirements: a Manifesto Eleonora Giunchiglia F. Imrie M. Schaar Thomas Lukasiewicz AI4TS OffRL VLM 34 5 0 07 Apr 2023
MLTEing Models: Negotiating, Evaluating, and Documenting Model and System Qualities Katherine R. Maffey Kyle Dotterrer Jennifer Niemann Iain J. Cruickshank Grace A. Lewis Christian Kastner 27 4 0 03 Mar 2023
Requirements Engineering for Machine Learning: A Review and Reflection Zhong Pei Lin Liu Chen Wang Jianmin Wang VLM 40 22 0 03 Oct 2022
Modeling Quality and Machine Learning Pipelines through Extended Feature Models Giordano dÁloisio A. Marco Giovanni Stilo 18 7 0 15 Jul 2022
STAMP 4 NLP -- An Agile Framework for Rapid Quality-Driven NLP Applications Development Philipp Kohl Oliver Schmidts Lars Klöser H. Werth Bodo Kraft Albert Zündorf VLM 17 1 0 16 Nov 2021
Collaboration Challenges in Building ML-Enabled Systems: Communication, Documentation, Engineering, and Process Nadia Nahar Shurui Zhou Grace A. Lewis Christian Kastner VLM 45 126 0 19 Oct 2021
Certification of embedded systems based on Machine Learning: A survey Guillaume Vidot Christophe Gabreau I. Ober Iulian Ober 11 12 0 14 Jun 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,675 0 05 Dec 2016
Neural Architecture Search with Reinforcement Learning Barret Zoph Quoc V. Le 271 5,327 0 05 Nov 2016
Recurrent Neural Networks for Multivariate Time Series with Missing Values Zhengping Che S. Purushotham Kyunghyun Cho David Sontag Yan Liu AI4TS 225 1,900 0 06 Jun 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,145 0 06 Jun 2015