Variational Learning of Gaussian Process Latent Variable Models through Stochastic Gradient Annealed Importance Sampling

13 August 2024

Papers citing "Variational Learning of Gaussian Process Latent Variable Models through Stochastic Gradient Annealed Importance Sampling"

8 / 8 papers shown

Title
Differentiable Annealed Importance Sampling and the Perils of Gradient Noise Guodong Zhang Kyle Hsu Jianing Li Chelsea Finn Roger C. Grosse 53 40 0 21 Jul 2021
Structured Stochastic Gradient MCMC Antonios Alexos Alex Boyd Stephan Mandt BDL 27 12 0 19 Jul 2021
Markovian Score Climbing: Variational Inference with KL(p\|\|q) C. A. Naesseth Fredrik Lindsten David M. Blei 137 54 0 23 Mar 2020
Stochastic Normalizing Flows Hao Wu Jonas Köhler Frank Noé 96 181 0 16 Feb 2020
Controlled Sequential Monte Carlo J. Heng A. Bishop George Deligiannidis Arnaud Doucet 55 72 0 28 Aug 2017
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 880 149,474 0 22 Dec 2014
Stochastic Gradient Hamiltonian Monte Carlo Tianqi Chen E. Fox Carlos Guestrin BDL 88 906 0 17 Feb 2014
Stochastic Variational Inference Matt Hoffman David M. Blei Chong-Jun Wang John Paisley BDL 204 2,616 0 29 Jun 2012