Dear all,
the 5th Season of the One World ABC www.warwick.ac.uk/oneworldabchttp://www.warwick.ac.uk/oneworldabc is about to start. We are working on the lineup, after having secured some exciting talks (more info to come). If you are interested in giving a talk or would like to suggest a speaker, please get in touch with Massimiliano Tamborrino (massimiliano.tamborrino@warwick.ac.uk) or any of the other organisers.
Our first speaker is Carlo Alberthttps://www.eawag.ch/en/about-us/portrait/organisation/staff/profile/carlo-albert/show/, who is talking about "Learning summary statistics for Bayesian inference with Autoencoders" on Thursday the 28th September at 9am UK time, with an abstract reported below.
The talk will be streamed on Zoom https://chalmers.zoom.us/j/69069218828 Password: 594071
We are looking forward to seeing you next Thursday, best, Massimiliano on the behalf of the OneWorldABC Organisers
Date: Thursday, September 28, 9am UK time Speaker: Carlo Alberthttps://www.eawag.ch/en/about-us/portrait/organisation/staff/profile/carlo-albert/show/, Swiss Federal Institute of Aquatic Science and Technology Title: Learning summary statistics for Bayesian inference with Autoencoders Abstract: In order for ABC to give accurate results and be efficient, we need summary statistics that retain most of the parameter-related information and cancel out most of the noise, respectively. For many scientific applications, we need strictly more summary statistics than model parameters to reach a satisfactory approximation of the posterior. Therefore, we propose to use a latent representation of deep neural networks based on Autoencoders as summary statistics. To create an incentive for the encoder to encode all the parameter-related information but not the noise, we give the decoder access to explicit or implicit information on the noise that has been used to generate the training data. We validate the approach empirically on two types of stochastic models, one being a member of the exponential family, the other one not.
------ Dr. Massimiliano Tamborrino Associate Professor Department of Statistics University of Warwick https://warwick.ac.uk/tamborrino