I don’t know much about this variant of Bayes, but the central idea is that we consider Bayes updating as a coherent betting rule and back everything else out from that. This gets us something like classic Bayes but with an even more austere approach to what probability is. I am interested in this because, following an insight of Susan Wei’s, I note that it might be an interesting way of understanding when foundation models do optimal inference, since most neural networks are best underst...
