John Salvatier

TL;DR: The performance of Theano is compared against Torch7 and TensorFlow on several machine learning models and recently-introduced functionalities and improvements are discussed.

TL;DR: This paper is a tutorial-style introduction to PyMC3, a new open source Probabilistic Programming framework written in Python that uses Theano to compute gradients via automatic dierentiation as well as compile probabilistic programs on-the-fly to C for increased speed.

TL;DR: The results indicate that, by using effective interventions, some countries could control the epidemic while avoiding stay-at-home orders, and this model accounts for uncertainty in key epidemiological parameters, such as the average delay from infection to death.

TL;DR: This user guide describes a Python package, PyMC, that allows users to efficiently code a probabilistic model and draw samples from its posterior distribution using Markov chain Monte Carlo techniques.

TL;DR: This article reported the results from a large survey of machine learning researchers on their beliefs about progress in AI and found that there is a 50% chance of AI outperforming humans in all tasks in 45 years and of automating all human jobs in 120 years with Asian respondents expecting these dates much sooner than North Americans.