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mackelab / mnle-for-ddms

Research code for Mixed Neural Likelihood Estimation (MNLE, Boelts et al. 2022)
GNU Affero General Public License v3.0
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Include value of experimental conditions (e.g. stimulus) in the training and posterior sampling for MNLE. #2

Closed alexgarciaduran closed 2 months ago

alexgarciaduran commented 1 year ago

Greetings,

Firstly, I would like to express my appreciation for this powerful tool. Currently, I am trying to fit a model (DDM) with three experimental conditions (e.g. stimulus) and 16 parameters. My problem is that I do not know how to sample from the posterior distributions considering these conditions. For the training, I just include them as additional inputs to the network, as suggested in the paper. Then, should I consider them as observed data (and also as inputs for the training)?

Thanks in advance, Alex

janfb commented 1 year ago

Hi @alexgarciaduran as mentioned in my email, there is a corresponding open issue in the SBI toolbox> https://github.com/mackelab/sbi/issues/717 I will work on fixing this soon!

alexgarciaduran commented 1 year ago

Thanks a lot!