Program
Schedule and Program
Schedule and Program
The workshop will start on Thursday 6 at 9.15am, and end on Friday 7 at 5.45pm. See two pdf below.
Keynote speakers
Keynote speakers
- Arnoldo Frigessi (SLIDES), University of Oslo, Norway. Personalized computer simulation of breast cancer treatment: a multiscale dynamic model informed by multi-source patient data
- Antonio Lijoi (SLIDES), University Bocconi, Milan, Italy. Compositions of random measures and their uses in Bayesian nonparametrics
- Sonia Petrone (SLIDES), University Bocconi, Milan, Italy. Bayesian predictive learning: exchangeability and beyond
Confirmed speakers
Confirmed speakers
- Simon Barthelmé (SLIDES), Gipsa-lab, Grenoble, France. Data sub-sampling with Determinantal Point Processes
- Annalisa Cadonna (SLIDES), WU Vienna, Austria. Spectral Density Estimation for Multiple Time Series
- Benjamin Guedj (SLIDES), Inria Lille - Nord Europe, France. A quasi-Bayesian perspective to Machine Learning
- Alessandra Guglielmi (SLIDES), Politecnico di Milano, Italy. Bayesian nonparametric models for clustering individuals with covariates
- Mayetri Gupta (SLIDES), University of Glasgow, UK. Bayesian clustering of skewed and multimodal data with applications to genomics.
- Claude Le Pape-Gardeux (SLIDES), Schneider Electric, Grenoble, France. Analytics artificial intelligence at Schneider Electric: powering the future of energy management & automation
- Consuelo Nava (SLIDES), UniversitĂ della Valle d'Aosta, Italy. A Bayesian mixed multinomial logit model for partially microsimulated data on labor supply
- Bernardo Nipoti (SLIDES), Trinity College Dublin, Ireland. Augmented conditional sampler for nonparametric mixture models
- Hien Nguyen (SLIDES), La Trobe University, Melbourne, Victoria, Australia. On approximations via convolution-defined mixture models
- Thibaud Rahier (SLIDES), Inria Grenoble & Schneider Electric, Grenoble, France. Screening strong pairwise relationships for fast Bayesian network structure learning.
- Daniel Tait (SLIDES), University of Edinburgh, UK. Multiplicative latent force models.
- Elodie Vernet (SLIDES), Ecole polytechnique, France. A Bayesian nonparametric approach for generalized Bradley-Terry models in random environment
![](https://www.google.com/images/icons/product/drive-32.png)
![](https://www.google.com/images/icons/product/drive-32.png)
Booklet of the conference