no code implementations • NeurIPS 2018 • Jian-Qiao Zhu, Adam N. Sanborn, Nick Chater
We propose that mental sampling is not done by simple MCMC, but is instead adapted to multimodal representations and is implemented by Metropolis-coupled Markov chain Monte Carlo (MC$^3$), one of the first algorithms developed for sampling from multimodal distributions.
no code implementations • 4 Aug 2017 • Paul M. B. Vitanyi, Nick Chater
But there is a more fundamental question: is the problem of inferring a probabilistic model from a sample possible even in principle?
no code implementations • 28 Nov 2013 • Paul M. B. Vitanyi, Nick Chater
TThe problem is to identify a probability associated with a set of natural numbers, given an infinite data sequence of elements from the set.
no code implementations • 24 Aug 2012 • Paul M. B. Vitanyi, Nick Chater
There is an effective procedure to identify by infinite recurrence a nonempty subset of the computable measures according to which the data is typical.
no code implementations • NeurIPS 2009 • Adam Sanborn, Nick Chater, Katherine A. Heller
Specifically, we present a rational model that does not assume dimensions, but learns the same type of dimensional generalizations that people display.
