Aki Vehtari
Institutionen för datateknik

Aki Vehtari

Teaching Researcher

Kontakt information

Postadress
Aalto SCI Computer Science Konemiehentie 2
Mobile phone
+358405333747
Full researcher profile
https://research.aalto.fi/...

Beskrivning

I'm co-leader of the Probabilistic Machine Learning Group at Aalto. We develop new methods for probabilistic modeling, Bayesian inference and machine learning. Our current focuses are in particular probabilistic programming, learning from multiple data sources, Bayesian model assessment and selection, approximate inference and information visualization. Our primary application areas are digital health and biology, neuroscience and user interaction.

I'm visiting professor at Technical University of Denmark (DTU), and I have a shared office at Columbia University in the City of New York. I'm member of development teams of Stan, ELFI, GPy and GPstuff.

Kompetensområden

Bayesian modeling Statistical analysis Epidemiology Brain signal analysis Machine learning

Utmärkelser

Award or honor granted for a specific work
Institutionen för datateknik
Jun 2016

2016 De Groot Prize The DeGroot Prize, in honor of Morris H ("Morrie" DeGroot, is awarded to the author or authors of an outstanding published book in Statistical Science

Invitation or ranking in competition
Institutionen för datateknik
Jan 2004

Member of the winning team (Särkkä, Vehtari & Lampinen) in Time Series Prediction Competition - The CATS Benchmark 2004

Forskargrupper

Professorship Vehtari A., Teaching Researcher
Helsinki Institute for Information Technology HIIT, Teaching Researcher
Probabilistic Machine Learning, Teaching Researcher

Publikationer

Institutionen för datateknik, Probabilistic Machine Learning, Professorship Vehtari A., Institutionen för teknisk fysik, Multiscale Statistical Physics

Nudged elastic band calculations accelerated with Gaussian process regression based on inverse inter-atomic distances

Publishing year: 2019 Journal of Chemical Theory and Computation
Professorship Vehtari A., Högskoleservice, Institutionen för datateknik, Probabilistic Machine Learning, Helsinki Institute for Information Technology HIIT, Centre of Excellence in Computational Inference, COIN

Pushing the Limits of Importance Sampling through Iterative Moment Matching

Publishing year: 2019 STATISTICS AND COMPUTING
Probabilistic Machine Learning, Helsinki Institute for Information Technology HIIT, Professorship Kaski S., Centre of Excellence in Computational Inference, COIN, Institutionen för datateknik, Professorship Vehtari A., Professorship Marttinen P.

Efficient acquisition rules for model-based approximate Bayesian computation

Publishing year: 2019 Bayesian Analysis
Institutionen för teknisk fysik, Computational Electronic Structure Theory, Probabilistic Machine Learning, Professorship Vehtari A., Institutionen för datateknik, Helsinki Institute for Information Technology HIIT

Deep Learning Spectroscopy

Publishing year: 2019 Advanced Science
Institutionen för datateknik, Centre of Excellence in Molecular Systems Immunology and Physiology Research Group, SyMMys, Professorship Lähdesmäki H., Centre of Excellence in Computational Inference, COIN, Probabilistic Machine Learning, Helsinki Institute for Information Technology HIIT, Professorship Vehtari A.

An additive Gaussian process regression model for interpretable non-parametric analysis of longitudinal data

Publishing year: 2019 Nature Communications
Professorship Vehtari A., Institutionen för datateknik, Högskoleservice, Probabilistic Machine Learning, Helsinki Institute for Information Technology HIIT, Centre of Excellence in Computational Inference, COIN

Variable selection for Gaussian processes via sensitivity analysis of the posterior predictive distribution

Publishing year: 2019 Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics
Institutionen för datateknik, Professorship Vehtari A., Helsinki Institute for Information Technology HIIT, Probabilistic Machine Learning

R-squared for Bayesian regression models

Publishing year: 2019 AMERICAN STATISTICIAN
Centre of Excellence in Computational Inference, COIN, Professorship Kaski S., Helsinki Institute for Information Technology HIIT, Probabilistic Machine Learning, Högskoleservice, Institutionen för datateknik, Professorship Vehtari A., Professorship Marttinen P.

Parallel Gaussian process surrogate method to accelerate likelihood-free inference

Publishing year: 2019 Bayesian Analysis
Centre of Excellence in Computational Inference, COIN, Professorship Kaski S., Helsinki Institute for Information Technology HIIT, Probabilistic Machine Learning, Högskoleservice, Institutionen för datateknik, Professorship Vehtari A., Finnish Center for Artificial Intelligence

Active Learning for Decision-Making from Imbalanced Observational Data

Publishing year: 2019 Proceedings of the 36th International Conference on Machine Learning
Probabilistic Machine Learning, Helsinki Institute for Information Technology HIIT, Professorship Kaski S., Centre of Excellence in Computational Inference, COIN, Institutionen för datateknik, Professorship Vehtari A., Professorship Marttinen P.

Gaussian process modelling in approximate bayesian computation to estimate horizontal gene transfer in Bacteria

Publishing year: 2018 Annals of Applied Statistics