Radford M. Neal is a prominent statistician and researcher known for his work in Bayesian statistics, machine learning, and computational methods. He is a professor at the University of Toronto and has made significant contributions to the development of algorithms for Bayesian inference, including Markov Chain Monte Carlo (MCMC) methods, such as the Hamiltonian Monte Carlo (HMC) method. Neal is also known for his work on Gaussian processes and other probabilistic models.
New to topics? Read the docs here!