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A Unifying Framework for Parallel and Distributed Processing in R using
  Futures
v1v2v3v4 (latest)

A Unifying Framework for Parallel and Distributed Processing in R using Futures

2 August 2020
Henrik Bengtsson
    AI4TS
ArXiv (abs)PDFHTML

Papers citing "A Unifying Framework for Parallel and Distributed Processing in R using Futures"

14 / 14 papers shown
Title
shapr: Explaining Machine Learning Models with Conditional Shapley Values in R and Python
shapr: Explaining Machine Learning Models with Conditional Shapley Values in R and Python
Martin Jullum
Lars Henry Berge Olsen
Jon Lachmann
Annabelle Redelmeier
TDIFAtt
169
3
0
02 Apr 2025
MOODE: An R Package for Multi-Objective Optimal Design of Experiments
MOODE: An R Package for Multi-Objective Optimal Design of Experiments
Vasiliki Koutra
Olga Egorova
S. Gilmour
Luzia A. Trinca
26
0
0
22 Dec 2024
Sequential Rank and Preference Learning with the Bayesian Mallows Model
Sequential Rank and Preference Learning with the Bayesian Mallows Model
Øystein Sørensen
Anja Stein
Waldir Leoncio Netto
David S. Leslie
100
0
0
18 Dec 2024
Chopin: An Open Source R-language Tool to Support Spatial Analysis on
  Parallelizable Infrastructure
Chopin: An Open Source R-language Tool to Support Spatial Analysis on Parallelizable Infrastructure
Insang Song
Kyle P. Messier
AI4CE
87
0
0
16 Dec 2024
Bayesian Multilevel Compositional Data Analysis: Introduction,
  Evaluation, and Application
Bayesian Multilevel Compositional Data Analysis: Introduction, Evaluation, and Application
Flora Le
Tyman Stanford
D. Dumuid
Joshua F. Wiley
33
4
0
07 May 2024
mlr3summary: Concise and interpretable summaries for machine learning
  models
mlr3summary: Concise and interpretable summaries for machine learning models
Susanne Dandl
Marc Becker
B. Bischl
Giuseppe Casalicchio
Ludwig Bothmann
26
0
0
25 Apr 2024
baskexact: An R package for analytical calculation of basket trial
  operating characteristics
baskexact: An R package for analytical calculation of basket trial operating characteristics
Lukas Baumann
27
1
0
26 Mar 2024
Big problems in spatio-temporal disease mapping: methods and software
Big problems in spatio-temporal disease mapping: methods and software
E. Orozco-Acosta
A. Adin
M. D. Ugarte
67
13
0
20 Jan 2022
clrng: A tool set for parallel random numbergeneration on GPUs in R
clrng: A tool set for parallel random numbergeneration on GPUs in R
Ruoyong Xu
Patrick R. Brown
P. LÉcuyer
LRM
16
0
0
17 Jan 2022
A framework for causal segmentation analysis with machine learning in
  large-scale digital experiments
A framework for causal segmentation analysis with machine learning in large-scale digital experiments
N. Hejazi
Wenjing Zheng
Sathyanarayan Anand
CML
39
3
0
01 Nov 2021
Hyperparameter Optimization: Foundations, Algorithms, Best Practices and
  Open Challenges
Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges
B. Bischl
Martin Binder
Michel Lang
Tobias Pielok
Jakob Richter
...
Theresa Ullmann
Marc Becker
A. Boulesteix
Difan Deng
Marius Lindauer
250
510
0
13 Jul 2021
Mutation is all you need
Mutation is all you need
Lennart Schneider
Florian Pfisterer
Martin Binder
B. Bischl
BDL
92
4
0
04 Jul 2021
JointAI: Joint Analysis and Imputation of Incomplete Data in R
JointAI: Joint Analysis and Imputation of Incomplete Data in R
N. Erler
D. Rizopoulos
E. Lesaffre
18
41
0
25 Jul 2019
missSBM: An R Package for Handling Missing Values in the Stochastic
  Block Model
missSBM: An R Package for Handling Missing Values in the Stochastic Block Model
P. Barbillon
J. Chiquet
Timothée Tabouy
53
2
0
28 Jun 2019
1