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DC-Check: A Data-Centric AI checklist to guide the development of
  reliable machine learning systems

DC-Check: A Data-Centric AI checklist to guide the development of reliable machine learning systems

9 November 2022
Nabeel Seedat
F. Imrie
M. Schaar
ArXivPDFHTML

Papers citing "DC-Check: A Data-Centric AI checklist to guide the development of reliable machine learning systems"

12 / 12 papers shown
Title
Large Process Models: A Vision for Business Process Management in the Age of Generative AI
Large Process Models: A Vision for Business Process Management in the Age of Generative AI
T. Kampik
C. Warmuth
Adrian Rebmann
Ron Agam
Lukas N. P. Egger
...
Han van der Aa
Artem Polyvyanyy
S. Rinderle-Ma
Ingo Weber
Matthias Weidlich
72
11
0
20 Jan 2025
Unlocking Historical Clinical Trial Data with ALIGN: A Compositional Large Language Model System for Medical Coding
Unlocking Historical Clinical Trial Data with ALIGN: A Compositional Large Language Model System for Medical Coding
Nabeel Seedat
Caterina Tozzi
Andrea Hita Ardiaca
M. Schaar
James Weatherall
Adam Taylor
96
0
0
20 Nov 2024
Matchmaker: Self-Improving Large Language Model Programs for Schema
  Matching
Matchmaker: Self-Improving Large Language Model Programs for Schema Matching
Nabeel Seedat
M. Schaar
29
2
0
31 Oct 2024
You can't handle the (dirty) truth: Data-centric insights improve
  pseudo-labeling
You can't handle the (dirty) truth: Data-centric insights improve pseudo-labeling
Nabeel Seedat
Nicolas Huynh
F. Imrie
Mihaela van der Schaar
31
0
0
19 Jun 2024
AI Competitions and Benchmarks: Dataset Development
AI Competitions and Benchmarks: Dataset Development
Romain Egele
Julio C. S. Jacques Junior
Jan N. van Rijn
Isabelle M Guyon
Xavier Baró
Albert Clapés
Prasanna Balaprakash
Sergio Escalera
T. Moeslund
Jun Wan
35
0
0
15 Apr 2024
DMLR: Data-centric Machine Learning Research -- Past, Present and Future
DMLR: Data-centric Machine Learning Research -- Past, Present and Future
Luis Oala
M. Maskey
Lilith Bat-Leah
Alicia Parrish
Nezihe Merve Gürel
...
Lora Aroyo
Ce Zhang
Joaquin Vanschoren
Isabelle Guyon
Peter Mattson
AI4CE
18
10
0
21 Nov 2023
Data Leakage and Evaluation Issues in Micro-Expression Analysis
Data Leakage and Evaluation Issues in Micro-Expression Analysis
Tuomas Varanka
Yante Li
Wei Peng
Guoying Zhao
AAML
17
5
0
21 Nov 2022
MoleculeNet: A Benchmark for Molecular Machine Learning
MoleculeNet: A Benchmark for Molecular Machine Learning
Zhenqin Wu
Bharath Ramsundar
Evan N. Feinberg
Joseph Gomes
C. Geniesse
Aneesh S. Pappu
K. Leswing
Vijay S. Pande
OOD
159
1,766
0
02 Mar 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
268
5,635
0
05 Dec 2016
Revisiting Classifier Two-Sample Tests
Revisiting Classifier Two-Sample Tests
David Lopez-Paz
Maxime Oquab
65
389
0
20 Oct 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
247
9,042
0
06 Jun 2015
MissForest - nonparametric missing value imputation for mixed-type data
MissForest - nonparametric missing value imputation for mixed-type data
D. Stekhoven
Peter Buhlmann
157
4,191
0
04 May 2011
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