Blog Archives

Custom Distribution Solutions

November 21, 2017
By
Custom Distribution Solutions

I (Aki) recently made a case study that demonstrates how to implement user defined probability functions in Stan language (case study, git repo). As an example I use the generalized Pareto distribution (GPD) to model extreme values of geomagnetic storm data from the World Data Center for Geomagnetism. Stan has had support for user defined […] The post Custom Distribution Solutions appeared first on Statistical Modeling, Causal Inference, and Social…

Read more »

Postdoc in Finland and NY to work on probabilistic inference and Stan!

October 13, 2017
By

I (Aki) got 2 year funding to hire a postdoc to work on validation of probabilistic inference approaches and model selection in Stan. Work would be done with Stan team in Aalto, Helsinki and Columbia, New York. We probably have PhD positions, too. The funding is part of the joint project with Antti Honkela and […] The post Postdoc in Finland and NY to work on probabilistic inference and Stan!…

Read more »

Tenure-Track or Tenured Prof. in Machine Learning in Aalto, Finland

October 9, 2017
By

This job advertisement for a position in Aalto, Finland, is by Aki We are looking for a professor to either further strengthen our strong research fields, with keywords including statistical machine learning, probabilistic modelling, Bayesian inference, kernel methods, computational statistics, or complementing them with deep learning. Collaboration with other fields is welcome, with local opportunities […] The post Tenure-Track or Tenured Prof. in Machine Learning in Aalto, Finland appeared first…

Read more »

Stacking, pseudo-BMA, and AIC type weights for combining Bayesian predictive distributions

April 11, 2017
By
Stacking, pseudo-BMA, and AIC type weights for combining Bayesian predictive distributions

This post is by Aki. We have often been asked in the Stan user forum how to do model combination for Stan models. Bayesian model averaging (BMA) by computing marginal likelihoods is challenging in theory and even more challenging in practice using only the MCMC samples obtained from the full model posteriors. Some users have […] The post Stacking, pseudo-BMA, and AIC type weights for combining Bayesian predictive distributions appeared…

Read more »

Research fellow, postdoc, and PhD positions in probabilistic modeling and machine learning in Finland

February 28, 2017
By

Probabilistic modeling and machine learning are strong in Finland. Now is your opportunity to join us in this cool country! There are several postdoc and research fellow positions open in probabilistic machine learning in Aalto University and University of Helsinki (deadline Marh 19). Some of the topics are related also to probabilistic programming and Stan […] The post Research fellow, postdoc, and PhD positions in probabilistic modeling and machine learning…

Read more »

Practical Bayesian model evaluation in Stan and rstanarm using leave-one-out cross-validation

October 21, 2016
By

Our (Aki, Andrew and Jonah) paper Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC was recently published in Statistics and Computing. In the paper we show why it’s better to use LOO instead of WAIC for model evaluation how to compute LOO quickly and reliably using the full posterior sample how Pareto smoothing importance […] The post Practical Bayesian model evaluation in Stan and rstanarm using leave-one-out cross-validation appeared…

Read more »

Tenure Track Professor in Machine Learning, Aalto University, Finland

October 14, 2016
By
Tenure Track Professor in Machine Learning, Aalto University, Finland

Posted by Aki. I promise that next time I’ll post something else than a job advertisement, but before that here’s another great opportunity to join Aalto Univeristy where I work, too. “We are looking for a professor to either further strengthen our strong research fields, with keywords including statistical machine learning, probabilistic modelling, Bayesian inference, […] The post Tenure Track Professor in Machine Learning, Aalto University, Finland appeared first on…

Read more »

Several postdoc positions in probabilistic modeling and machine learning in Aalto, Helsinki

September 8, 2016
By

This post is by Aki In addition to the postdoc position I advertised recently, now Aalto University and University of Helsinki have 20 more open postdoc and research fellow positions. Many of the positions are in probabilistic models and machine learning. You could work with me (I’m also part of HIIT), but I can also […] The post Several postdoc positions in probabilistic modeling and machine learning in Aalto, Helsinki…

Read more »

R demos for BDA3

September 6, 2016
By

Last year we published some Matlab/Octave and Python demos for BDA3. During the summer my student Markus Paasiniemi ported these demos to R. New R BDA3 demos are now available in github. We hope these are helpful for someone. They are now just R code, although R Markdown would be cool. Btw. we are expecting […] The post R demos for BDA3 appeared first on Statistical Modeling, Causal Inference, and…

Read more »

Postdoc in Finland with Aki

August 24, 2016
By

I’m looking for a postdoc to work with me at Aalto University, Finland. The person hired will participate in research on Gaussian processes, functional constraints, big data, approximative Bayesian inference, model selection and assessment, deep learning, and survival analysis models (e.g. cardiovascular diseases and cancer). Methods will be implemented mostly in GPy and Stan. The […] The post Postdoc in Finland with Aki appeared first on Statistical Modeling, Causal Inference,…

Read more »


Subscribe

Email:

  Subscribe