David Issa Mattos | DeepAI

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∙ 07/01/2022

Bayesian causal inference in automotive software engineering and online evaluation

Randomised field experiments, such as A/B testing, have long been the go...

0 Yuchu Liu, et al. ∙

∙ 04/19/2022

On the Use of Causal Graphical Models for Designing Experiments in the Automotive Domain

Randomized field experiments are the gold standard for evaluating the im...

0 David Issa Mattos, et al. ∙

∙ 09/26/2021

Bayesian propensity score matching in automotive embedded software engineering

Randomised field experiments, such as A/B testing, have long been the go...

0 Yuchu Liu, et al. ∙

∙ 07/06/2021

Size matters? Or not: A/B testing with limited sample in automotive embedded software

A/B testing is gaining attention in the automotive sector as a promising...

0 Yuchu Liu, et al. ∙

∙ 04/15/2021

On the Assessment of Benchmark Suites for Algorithm Comparison

Benchmark suites, i.e. a collection of benchmark functions, are widely u...

0 David Issa Mattos, et al. ∙

∙ 01/27/2021

Bayesian Paired-Comparison with the bpcs Package

This article introduces the bpcs R package (Bayesian Paired Comparison i...

0 David Issa Mattos, et al. ∙

∙ 10/08/2020

Statistical Models for the Analysis of Optimization Algorithms with Benchmark Functions

Frequentist statistical methods, such as hypothesis testing, are standar...

0 David Issa Mattos, et al. ∙

∙ 10/09/2019

Engineering for a Science-Centric Experimentation Platform

Netflix is an internet entertainment service that routinely employs expe...

0 Nikos Diamantopoulos, et al. ∙

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