76 citations · 203 across the 11 of their papers we have counts for
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stat.ML2015★ 13 cited
Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian Sampling
Xiaocheng Shang, Zhanxing Zhu, Benedict Leimkuhler +1
Monte Carlo sampling for Bayesian posterior inference is a common approach used in machine learning. The Markov Chain Monte Carlo procedures that are used are often discrete-time a…
math.NA2015★ 29 cited
Adaptive Thermostats for Noisy Gradient Systems
Benedict Leimkuhler, Xiaocheng Shang
We study numerical methods for sampling probability measures in high dimension where the underlying model is only approximately identified with a gradient system. Extended stochast…