Fetching the paper…
Reading the bibliography…
Bayesian methods are appealing in their flexibility in modeling complex data and ability in capturing uncertainty in parameters.
Bayesian conditionalisation and the principle of minimum information
P. M. Williams · 1980
Earlier work this paper cites.
Nonparametric Density Estimation: The L 1 L_{1} View
L. Devroye and L. Györfi · 1985
Earlier work this paper cites.
Optimal Information Processing and Bayes’s Theorem
A. Zellner · 1988
Earlier work this paper cites.
Probabilistic inference using Markov chain Monte Carlo methods
R. M. Neal · 1993
Earlier work this paper cites.
Information theoretic determination of minimax rates of convergence
A. Barron and Y. Yang · 1995
Earlier work this paper cites.
Kernel Smoothing
M. P. Wand and M. C. Jones · 1995
Earlier work this paper cites.
On minimax wavelet estimators
B. Delyon and A. Juditsky · 1996
Earlier work this paper cites.
A variational approach to bayesian logistic regression models and their extensions
T. Jaakkola and M. I. Jordan · 1997
Earlier work this paper cites.
An introduction to variational methods for graphical models
M. I. Jordan, Z. Gharamani, T. S. Jaakkola, and L. K. Saul · 1998
Earlier work this paper cites.
Learning in graphical models
T. S. Jaakkola and M. I. Jordon · 1999
Earlier work this paper cites.
Sequential Monte Carlo Methods in Practice
A. Doucet, N. de Freitas, and N. Gordon · 2001
Earlier work this paper cites.
Expectation Propagation for approximative Bayesian inference
T. Minka · 2001
Earlier work this paper cites.
Defining priors for distributions using dirichlet diffusion trees
R. M. Neal · 2001
Earlier work this paper cites.
A sequential particle filter method for static models
N. Chopin · 2002
Earlier work this paper cites.
A survey of convergence results on particle filtering methods for practitioners
D. Crisan and A. Doucet · 2002
Earlier work this paper cites.
On choosing and bounding probability metrics
A. Gibbs and F. E.Su · 2002
Cited alongside, same era.
Nonparametric belief propagation
E. Sudderth, A. Ihler, W. Freeman, and A. Willsky · 2003
Cited alongside, same era.
Stability and uniform approximation of nonlinear filters using the hilbert metric and application to particle filters
F. L. Gland and N. Oudjane · 2004
Cited alongside, same era.
Divergence measures and message passing
T. Minka · 2005
Cited alongside, same era.
A unifying view of sparse approximate gaussian process regression
J. Quiñonero-Candela and C. E. Rasmussen · 2005
Cited alongside, same era.
A one-pass sequential monte carlo method for bayesian analysis of massive datasets
S. Balakrishnan and D. Madigan · 2006
Cited alongside, same era.
Scalable inference in latent variable models
A. Ahmed, M. Aly, J. Gonzalez, S. Narayanamurthy, and A. J. Smola · 2012
Later among the works it cites.
Bayesian posterior sampling via stochastic gradient fisher scoring
S. Ahn, A. Korattikara, and M. Welling · 2012
Later among the works it cites.
Nonparametric variational inference
S. Gershman, M. Hoffman, and D. M. Blei · 2012
Later among the works it cites.
Sparse stochastic inference for latent dirichlet allocation
D. Mimno, M. Hoffman, and D. Blei · 2012
Later among the works it cites.
Variational bayesian inference with stochastic search
J. W. Paisley, D. M. Blei, and M. I. Jordan · 2012
Later among the works it cites.
Gaussian processes for big data
J. Hensman, N. Fusi, and N. D. Lawrence · 2013
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Sequential monte carlo samplers
P. Del Moral, A. Doucet, and A. Jasra · 2006
Cited alongside, same era.
Bayesian auxiliary variable models for binary and multinomial regression
C. C. Holmes and L. Held · 2006
Cited alongside, same era.
Graphical models, exponential families, and variational inference
M. J. Wainwright and M. I. Jordan · 2008
Cited alongside, same era.
Online inference of topics with latent dirichlet allocation
K. R. Canini, L. Shi, and T. L. Griff iths · 2009
Cited alongside, same era.
Particle belief propagation
A. Ihler and D. McAllester · 2009
Cited alongside, same era.
Robust stochastic approximation approach to stochastic programming
A. Nemirovski, A. Juditsky, G. Lan, and A. Shapiro · 2009
Cited alongside, same era.
Stochastic variational inference
M. D. Hoffman, D. M. Blei, C. Wang, and J. Paisley · 2013
Later among the works it cites.
Stochastic gradient Riemannian Langevin dynamics on the probability simplex
S. Patterson and Y. W. Teh · 2013
Later among the works it cites.
Stochastic Gradient Hamiltonian Monte Carlo
T. Chen, E. B. Fox, and C. Guestrin · 2014
Later among the works it cites.
Bayesian sampling using stochastic gradient thermostats
N. Ding, Y. Fang, R. Babbush, C. Chen, R. D. Skeel, and H. Neven · 2014
Later among the works it cites.
Firefly monte carlo: Exact MCMC with subsets of data
D. Maclaurin and R. P. Adams · 2014
Later among the works it cites.
Consistency and fluctuations for stochastic gradient Langevin dynamics
Y. W. Teh, A. H. Thiéry, and S. J. Vollmer · 2014
Later among the works it cites.
Bayesian inference with posterior regularization and applications to infinite latent svms
J. Zhu, N. Chen, and E. P. Xing · 2014
Later among the works it cites.
Expectation particle belief propagation
T. Lienart, Y. W. Teh, and A. Doucet · 2015
Closest in time.
(non-) asymptotic properties of stochastic gradient langevin dynamics
S. J. Vollmer, K. C. Zygalakis and Y. W. Teh · 2015
Closest in time.