Organizers

Organizers: Aki Vehtari and Arto Klami

Talks

Probabilistic Programming and Stan

Abstract: Probabilistic programming (PP) makes it easy to write new probabilistic models and PP frameworks then allow automated inference for those models. I describe the generic idea of PP, give some examples of software frameworks designed for different PP purposes, and focus more on recent development in Stan.

Speaker: Aki Vehtari

Automated Variational Inference

Abstract: Automated inference for generic models which can be programmed with probabilistic programming languages is challenging. I describe methods based on modern variational inference which are used to speed-up inference for big data.

Speaker: Arto Klami

Flash Talks

ELFI – Engine for Likelihood Free Inference

Abstract: ELFI – Engine for Likelihood Free Inference provides a probabilistic programming framework for combining probabilistic models with stochastic simulators and performs automated inference using efficient likelihood free inference algorithms.

Speaker: Henri Vuollekoski