31 citations · 39 across the 4 of their papers we have counts for
4 papers
Sequential Monte Carlo Learning for Time Series Structure Discovery
Feras A. Saad, Brian J. Patton, Matthew D. Hoffman +2
This paper presents a new approach to automatically discovering accurate models of complex time series data. Working within a Bayesian nonparametric prior over a symbolic space of…
Focusing on Difficult Directions for Learning HMC Trajectory Lengths
Pavel Sountsov, Matt D. Hoffman
Hamiltonian Monte Carlo (HMC) is a premier Markov Chain Monte Carlo (MCMC) algorithm for continuous target distributions. Its full potential can only be unleashed when its problem-…
Synthesizing Diverse, High-Quality Audio Textures
Joseph Antognini, Matt Hoffman, Ron J. Weiss
Texture synthesis techniques based on matching the Gram matrix of feature activations in neural networks have achieved spectacular success in the image domain. In this paper we ext…
New inference strategies for solving Markov Decision Processes using reversible jump MCMC
Matthias Hoffman, Hendrik Kueck, Nando de Freitas +1
In this paper we build on previous work which uses inferences techniques, in particular Markov Chain Monte Carlo (MCMC) methods, to solve parameterized control problems. We propose…