Fetching the paper…
Reading the bibliography…
Our article considers a Gaussian variational approximation of the posterior density in a high-dimensional state space model.
High-dimensional copula variational approximation through transformation
Smith, M. S., Loaiza-Maya, R., and Nott, D. J. (2019) · 1904
Earlier work this paper cites.
Conditionally structured variational Gaussian approximation with importance weights
Tan, L. S.-L., Bhaskaran, A., and Nott, D. J. (2019) · 1904
Earlier work this paper cites.
Inverting modified matrices
Woodbury, M. A. (1950) · 1950
Earlier work this paper cites.
A stochastic approximation method
Robbins, H. and Monro, S. (1951) · 1951
Earlier work this paper cites.
The elimination matrix: some lemmas and applications
Magnus, J. R. and Neudecker, H. (1980) · 1980
Earlier work this paper cites.
On differentiating eigenvalues and eigenvectors
Magnus, J. R. (1985) · 1985
Earlier work this paper cites.
Matrix differential calculus with applications to simple, Hadamard, and Kronecker products
Magnus, J. R. and Neudecker, H. (1985) · 1985
Earlier work this paper cites.
Identifiability of factor analysis: Some results and open problems
Shapiro, A. (1985) · 1985
Earlier work this paper cites.
A Monte Carlo approach to nonnormal and nonlinear state-space modeling
Carlin, B. P., Polson, N. G., and Stoffer, D. S. (1992) · 1992
Earlier work this paper cites.
Inference from iterative simulation using multiple sequences
Gelman, A. and Rubin, D. B. (1992) · 1992
Earlier work this paper cites.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
Williams, R. J. (1992) · 1992
Earlier work this paper cites.
Novel approach to nonlinear/non-Gaussian Bayesian state estimation
Gordon, N. J., Salmond, D. J., and Smith, A. F. (1993) · 1993
Earlier work this paper cites.
On Gibbs sampling for state space models
Carter, C. K. and Kohn, R. (1994) · 1994
Earlier work this paper cites.
Measuring the pricing error of the arbitrage pricing theory
Geweke, J. and Zhou, G. (1996) · 1996
Earlier work this paper cites.
Ensemble learning for multi-layer networks
Barber, D. and Bishop, C. M. (1998) · 1998
Earlier work this paper cites.
Inferring parameters and structure of latent variable models by variational Bayes
Attias, H. (1999) · 1999
Earlier work this paper cites.
An introduction to variational methods for graphical models
Jordan, M. I., Ghahramani, Z., Jaakkola, T. S., and Saul, L. K. (1999) · 1999
Earlier work this paper cites.
A dimension-reduced approach to space-time Kalman filtering
Wikle, C. and Cressie, N. (1999) · 1999
Earlier work this paper cites.
Bayesian dynamic factor models and portfolio allocation
Aguilar, O. and West, M. (2000) · 2000
Earlier work this paper cites.
Bayesian model selection for support vector machines, Gaussian processes and other kernel classifiers
Seeger, M. (2000) · 2000
Earlier work this paper cites.
Estimation of population growth or decline in genetically monitored populations
Beaumont, M. A. (2003) · 2003
Earlier work this paper cites.
Variational message passing
Winn, J. and Bishop, C. M. (2005) · 2005
Earlier work this paper cites.
CODA: convergence diagnosis and output analysis for MCMC
Plummer, M., Best, N., Cowles, K., and Vines, K. (2006) · 2006
Cited alongside, same era.
Hierarchical Bayesian spatio-temporal models for population spread
Wikle, C. K. and Hooten, M. B. (2006) · 2006
Cited alongside, same era.
High-dimensional sparse factor modeling: Applications in gene expression genomics
Carvalho, C. M., Chang, J., Lucas, J. E., Nevins, J. R., Wang, Q., and West, M. (2008) · 2008
Cited alongside, same era.
Spatial dynamic factor analysis
Lopes, H. F., Salazar, E., and Gamerman, D. (2008) · 2008
Cited alongside, same era.
The pseudo-marginal approach for efficient Monte Carlo computations
Andrieu, C. and Roberts, G. (2009) · 2009
Cited alongside, same era.
The variational Gaussian approximation revisited
Opper, M. and Archambeau, C. (2009) · 2009
Cited alongside, same era.
Auto-encoding variational Bayes
Kingma, D. P. and Welling, M. (2014) · 2014
Later among the works it cites.
A flexible observed factor model with separate dynamics for the factor volatilities and their correlation matrix
Ku, Y.-C., Bloomfield, P., and Ghosh, S. K. (2014) · 2014
Later among the works it cites.
Black box variational inference
Ranganath, R., Gerrish, S., and Blei, D. M. (2014) · 2014
Later among the works it cites.
Stochastic backpropagation and approximate inference in deep generative models
Rezende, D. J., Mohamed, S., and Wierstra, D. (2014) · 2014
Later among the works it cites.
Doubly stochastic variational Bayes for non-conjugate inference
Titsias, M. and Lázaro-Gredilla, M. (2014) · 2014
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Particle Markov chain Monte Carlo methods
Andrieu, C., Doucet, A., and Holenstein, R. (2010) · 2010
Cited alongside, same era.
Large-scale machine learning with stochastic gradient descent
Bottou, L. (2010) · 2010
Cited alongside, same era.
Bounded approximations for marginal likelihoods
Ji, C., Shen, H., and West, M. (2010) · 2010
Cited alongside, same era.
Explaining variational approximations
Ormerod, J. T. and Wand, M. P. (2010) · 2010
Cited alongside, same era.
Latent variable models and factor analysis: A unified approach, 3rd edition
Bartholomew, D. J., Knott, M., and Moustaki, I. (2011) · 2011
Cited alongside, same era.
Statistics for Spatio-Temporal Data
Cressie, N. and Wikle, C. (2011) · 2011
Cited alongside, same era.
Doucet, A., Pitt, M. K., Deligiannidis, G., and Kohn, R. (2015) · 2015
Later among the works it cites.
Local expectation gradients for black box variational inference
Titsias, M. and Lázaro-Gredilla, M. (2015) · 2015
Later among the works it cites.
Black box variational inference for state space models
Archer, E., Park, I. M., Buesing, L., Cunningham, J., and Paninski, L. (2016) · 2016
Later among the works it cites.
A note on the vec operator applied to unbalanced block-structured matrices
Caswell, H. and van Daalen, S. F. (2016) · 2016
Later among the works it cites.
Variational Gaussian copula inference
Han, S., Liao, X., Dunson, D. B., and Carin, L. C. (2016) · 2016
Later among the works it cites.
Variational inference: A review for statisticians
Blei, D. M., Kucukelbir, A., and McAuliffe, J. D. (2017) · 2017
Later among the works it cites.
Automatic differentiation variational inference
Kucukelbir, A., Tran, D., Ranganath, R., Gelman, A., and Blei, D. M. (2017) · 2017
Later among the works it cites.
Variational boosting: Iteratively refining posterior approximations
Miller, A. C., Foti, N. J., and Adams, R. P. (2017) · 2017
Later among the works it cites.
Sticking the landing: Simple, lower-variance gradient estimators for variational inference
Roeder, G., Wu, Y., and Duvenaud, D. (2017) · 2017
Later among the works it cites.
Gaussian variational approximation with sparse precision matrices
Tan, S. L. and Nott, D. J. (2017) · 2017
Later among the works it cites.
Gaussian variational approximation with a factor covariance structure
Ong, V. M.-H., Nott, D. J., and Smith, M. S. (2018) · 2018
Closest in time.
Inference via low-dimensional couplings
Spantini, A., Bigoni, D., and Marzouk, Y. (2018) · 2018
Closest in time.
Convergence rates of variational posterior distributions
Zhang, F. and Gao, C. (2018) · 2018
Closest in time.
Banded matrix operators for gaussian markov models in the automatic differentiation era
Durrande, N., Adam, V., Bordeaux, L., Eleftheriadis, S., and Hensman, J. (2019) · 2019
Closest in time.
Frequentist consistency of variational Bayes
Wang, Y. and Blei, D. M. (2019) · 2019
Closest in time.
Variance reduction properties of the reparameterization trick
Xu, M., Quiroz, M., Kohn, R., and Sisson, S. A. (2019) · 2019
Closest in time.