Actually kind of the opposite idea. So called "uninformative priors" can be considered a form or model regularization in that they prevent the model from fittin

Actually kind of the opposite idea. So called "uninformative priors" can be considered a form or model regularization in that they prevent the model from fitting the data too well...they spread the posterior distribution out. Weakly informative priors like a broad normal distribution are also popular and may yield better results.