This discussion paper aims to address the policy implications of emerging large language models such as ChatGPT. As academic researchers active in the field of AI research, we are uniquely positioned to understand the technology involved and to consider its potential implications. Given the...

The multiple try Metropolis (MTM) method is a generalization of the classical Metropolis–Hastings algorithm in which the next state of the chain is chosen among a set of samples, according to normalized weights. In the literature, several extensions have been proposed. In this work, we show...

The multi-point Metropolis algorithm is an advanced MCMC technique based on drawing several correlated samples at each step and choosing one of them according to some normalized weights. We propose a variation of this technique where the weight functions are not specified, i.e., the analytic...