A tutorial on optimization, model fitting, and model comparison for neuroscience

8 May 2019, 10.00 AM - 8 May 2019, 12.00 PM

Luigi Acerbi (International Brain Laboratory)

Geographical Sciences Building G.11N SR1

Hosted by the Neural Dynamics Forum.

In terms of topics, I will give a brief introduction to likelihood-based modeling and then focus on model fitting by maximum-likelihood, with a quick overview of optimization methods including state-of-the-art Bayesian optimization and BADS [1]. I will then talk briefly about model selection metrics, pros and cons. Depending on the audience and if we have time, I will also touch upon more advanced topics, such as Bayesian posterior estimation and approximate inference techniques, such as VBMC [2] (on which I am giving a talk at 2pm on the same day at Queens building). The tutorial will be in Matlab, but many of the concepts (if not directly the techniques) are language-free and can be easily applied in your favourite language, be it Python, Julia, R, or BASIC.

[1] BADS repo: https://github.com/lacerbi/bads
[2] VBMC repo: https://github.com/lacerbi/vbmc 

More can be found here: http://luigiacerbi.com/tutorials/

Contact information

For further information contact Anne-Lenne Sax.

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