Aki Vehtari

Aki Vehtari

Aalto-yliopisto

H-index: 55

Europe-Finland

About Aki Vehtari

Aki Vehtari, With an exceptional h-index of 55 and a recent h-index of 46 (since 2020), a distinguished researcher at Aalto-yliopisto, specializes in the field of Bayesian analysis, Bayesian statistics, Bayesian workflow, Gaussian processes.

His recent articles reflect a diverse array of research interests and contributions to the field:

Modeling public opinion over time and space: Trust in state institutions in Europe, 1989-2019

Supporting Bayesian modelling workflows with iterative filtering for multiverse analysis

Active Statistics: Stories, Games, Problems, and Hands-on Demonstrations for Applied Regression and Causal Inference

Model validation for aggregate inferences in out-of-sample prediction

Past, Present and Future of Software for Bayesian Inference

Detecting and diagnosing prior and likelihood sensitivity with power-scaling

Raw signal segmentation for estimating RNA modifications and structures from Nanopore direct RNA sequencing data

Bird tolerance to humans in open tropical ecosystems

Aki Vehtari Information

University

Position

Associate Professor

Citations(all)

60190

Citations(since 2020)

29402

Cited By

41170

hIndex(all)

55

hIndex(since 2020)

46

i10Index(all)

139

i10Index(since 2020)

116

Email

University Profile Page

Google Scholar

Aki Vehtari Skills & Research Interests

Bayesian analysis

Bayesian statistics

Bayesian workflow

Gaussian processes

Top articles of Aki Vehtari

Modeling public opinion over time and space: Trust in state institutions in Europe, 1989-2019

Survey Research Methods

2024/4/16

Lauren Kennedy
Lauren Kennedy

H-Index: 5

Aki Vehtari
Aki Vehtari

H-Index: 36

Supporting Bayesian modelling workflows with iterative filtering for multiverse analysis

arXiv preprint arXiv:2404.01688

2024/4/2

Antti Oulasvirta
Antti Oulasvirta

H-Index: 41

Aki Vehtari
Aki Vehtari

H-Index: 36

Active Statistics: Stories, Games, Problems, and Hands-on Demonstrations for Applied Regression and Causal Inference

2024/3/31

Andrew Gelman
Andrew Gelman

H-Index: 31

Aki Vehtari
Aki Vehtari

H-Index: 36

Model validation for aggregate inferences in out-of-sample prediction

2024/2/15

Past, Present and Future of Software for Bayesian Inference

2024/2

Detecting and diagnosing prior and likelihood sensitivity with power-scaling

Statistics and Computing

2024/2

Aki Vehtari
Aki Vehtari

H-Index: 36

Raw signal segmentation for estimating RNA modifications and structures from Nanopore direct RNA sequencing data

bioRxiv

2024

Aki Vehtari
Aki Vehtari

H-Index: 36

Lu Cheng
Lu Cheng

H-Index: 13

Using reference models in variable selection

Computational Statistics

2023/3

Aki Vehtari
Aki Vehtari

H-Index: 36

Practical Hilbert space approximate Bayesian Gaussian processes for probabilistic programming

Statistics and Computing

2023/2

Arno Solin
Arno Solin

H-Index: 21

Aki Vehtari
Aki Vehtari

H-Index: 36

Crossvalidatory model selection for Bayesian autoregressions with exogenous regressors

arXiv preprint arXiv:2301.08276

2023/1/19

Projection predictive variable selection for discrete response families with finite support

arXiv preprint arXiv:2301.01660

2023/1/4

Aki Vehtari
Aki Vehtari

H-Index: 36

Simulation-based calibration checking for Bayesian computation: The choice of test quantities shapes sensitivity

Bayesian Analysis

2023/1

Andrew Gelman
Andrew Gelman

H-Index: 31

Aki Vehtari
Aki Vehtari

H-Index: 36

An importance sampling approach for reliable and efficient inference in Bayesian ordinary differential equation models

Stat

2023/1

Aki Vehtari
Aki Vehtari

H-Index: 36

Scoring multilevel regression and postratification based population and subpopulation estimates

arXiv preprint arXiv:2312.06334

2023/12/11

Bayesian cross-validation by parallel Markov chain Monte Carlo

arXiv preprint arXiv:2310.07002

2023/10/10

Efficient estimation and correction of selection-induced bias with order statistics

arXiv preprint arXiv:2309.03742

2023/9/7

Aki Vehtari
Aki Vehtari

H-Index: 36

Fast methods for posterior inference of two-group normal-normal models

Bayesian Analysis

2023/9

Unbiased estimator for the variance of the leave-one-out cross-validation estimator for a Bayesian normal model with fixed variance

Communications in Statistics-Theory and Methods

2023/8/18

Måns Magnusson
Måns Magnusson

H-Index: 29

Aki Vehtari
Aki Vehtari

H-Index: 36

Robust and efficient projection predictive inference

arXiv preprint arXiv:2306.15581

2023/6/27

Aki Vehtari
Aki Vehtari

H-Index: 36

See List of Professors in Aki Vehtari University(Aalto-yliopisto)

Co-Authors

academic-engine