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We propose a kernel-based nonparametric test of relative goodness of fit, where the goal is to compare two models, both of which may have unobserved latent variables, such that the marginal distribution of the observed variables is intractable.
In Advances in Neural Information Processing Systems
Huggins, J. and Mackey, L. (2018) Random feature Stein discrepancies · 1909
Earlier work this paper cites.
arXiv preprint arXiv:1912.11554
Phan, D., Pradhan, N. and Jankowiak, M. (2019) Composable effects for flexible and accelerated probabilistic programming in NumPyro · 1912
Earlier work this paper cites.
Mathematical Proceedings of the Cambridge Philosophical Society
Fisher, R. A. (1925) Theory of statistical estimation · 1925
Earlier work this paper cites.
Ann. Math. Statist
Hoeffding, W. (1948) A class of statistics with asymptotically normal distribution · 1948
Earlier work this paper cites.
Transactions of the American Mathematical Society
Aronszajn, N. (1950) Theory of reproducing kernels · 1950
Earlier work this paper cites.
Third edition. Clarendon Press, Oxford
Jeffreys, H. (1961) Theory of probability · 1961
Earlier work this paper cites.
In Proceedings of the Sixth Berkeley Symposium on Mathematical Statistics and Probability (Univ. California, Berkeley, Calif., 1970/1971), Vol. II: Probability theory
Stein, C. (1972) A bound for the error in the normal approximation to the distribution of a sum of dependent random variables · 1971
Earlier work this paper cites.
The Annals of Probability
Chen, L. H. Y. (1975) Poisson approximation for dependent trials · 1975
Earlier work this paper cites.
Journal of the Royal Statistical Society: Series B (Methodological)
Dempster, A. P., Laird, N. M. and Rubin, D. B. (1977) Maximum likelihood from incomplete data via the EM algorithm · 1977
Earlier work this paper cites.
The Annals of Statistics
Callaert, H. and Janssen, P. (1978) The Berry-Esseen theorem for U-statistics · 1978
Earlier work this paper cites.
The Annals of Statistics
Schwarz, G. (1978) Estimating the dimension of a model · 1978
Earlier work this paper cites.
The Annals of Statistics
Efron, B. and Stein, C. (1981) The jackknife estimate of variance · 1981
Earlier work this paper cites.
In Recent Advances in Statistics
Ferguson, T. S. (1983) Bayesian density estimation by mixtures of normal distributions · 1983
Earlier work this paper cites.
Institute of Mathematical Statistics, Hayward, CA
— (1986) Approximate computation of expectations · 1986
Earlier work this paper cites.
Physics Letters B
Duane, S., Kennedy, A., Pendleton, B. J. and Roweth, D. (1987) Hybrid Monte Carlo · 1987
Earlier work this paper cites.
Journal of Applied Probability
Barbour, A. D. (1988) Stein’s method and Poisson process convergence · 1988
Earlier work this paper cites.
Proceedings of the IEEE
Rabiner, L. R. (1989) A tutorial on hidden Markov models and selected applications in speech recognition · 1989
Earlier work this paper cites.
The Annals of Probability
Götze, F. (1991) On the rate of convergence in the multivariate CLT · 1991
Earlier work this paper cites.
John Wiley & Sons, Inc
Basilevsky, A. (1994) Statistical factor analysis and related methods · 1994
Earlier work this paper cites.
Journal of the Royal Statistical Society. Series B, (Statistical Methodology)
Besag, J. (1994) Comments on ’Representations of knowledge in complex systems’ by U. Grenander and M.I. Miller · 1994
Earlier work this paper cites.
Chapman & Hall
Gilks, W. R., Richardson, S. and Spiegelhalter, D. J. (1995) Markov chain Monte Carlo in practice · 1995
Earlier work this paper cites.
Biometrika
Green, P. J. (1995) Reversible jump Markov chain Monte Carlo computation and Bayesian model determination · 1995
Earlier work this paper cites.
Journal of the American Statistical Association
Kass, R. E. and Raftery, A. E. (1995) Bayes factors · 1995
Earlier work this paper cites.
Bernoulli
Roberts, G. O. and Tweedie, R. L. (1996) Exponential convergence of Langevin distributions and their discrete approximations · 1996
Earlier work this paper cites.
Advances in Applied Probability
Müller, A. (1997) Integral probability metrics and their generating classes of functions · 1997
Earlier work this paper cites.
In Advances in Neural Information Processing Systems
Roweis, S. T. (1997) EM algorithms for PCA and SPCA · 1997
Earlier work this paper cites.
Journal of the Japan Statistical Society
Maesono, Y. (1998) Asymptotic mean square errors of variance estimators for U-statistics and their Edgeworth expansions · 1998
Earlier work this paper cites.
Journal of the Royal Statistical Society. Series B, (Statistical Methodology)
Tipping, M. and Bishop, C. (1999) Probabilistic principal component analysis · 1999
Earlier work this paper cites.
Cambridge University Press
van der Vaart, A. W. (2000) Asymptotic statistics · 2000
Earlier work this paper cites.
Statistics and Computing
Neal, R. M. (2001) Annealed importance sampling · 2001
Earlier work this paper cites.
Journal of Machine Learning Research
Blei, D., Ng, A. and Jordan, M. (2003) Latent Dirichlet allocation · 2003
Earlier work this paper cites.
Probability Surveys
Roberts, G. O. and Rosenthal, J. S. (2004) General state space Markov chains and MCMC algorithms · 2004
Cited alongside, same era.
Springer, third edn
Lehmann, E. L. and Romano, J. P. (2005) Testing statistical hypotheses · 2005
Cited alongside, same era.
Journal of Mathematical Sciences
Kantorovich, L. V. (2006) On the translocation of masses · 2006
Cited alongside, same era.
Biometrika
Møller, J., Pettitt, A. N., Reeves, R. and Berthelsen, K. K. (2006) An efficient Markov chain Monte Carlo method for distributions with intractable normalising constants · 2006
Cited alongside, same era.
In Proceedings of the Twenty-Second Conference on Uncertainty in Artificial Intelligence
Murray, I., Ghahramani, Z. and MacKay, D. J. C. (2006) MCMC for doubly-intractable distributions · 2006
Cited alongside, same era.
John Wiley & Sons, Inc
Kowalski, J. and Tu, X. M. (2007) Modern applied U-statistics · 2007
Cited alongside, same era.
In Proceedings of The 33rd International Conference on Machine Learning
Liu, Q., Lee, J. and Jordan, M. (2016) A kernelized Stein discrepancy for goodness-of-fit tests · 2016
Later among the works it cites.
In Advances in Neural Information Processing Systems
Ranganath, R., Tran, D., Altosaar, J. and Blei, D. (2016) Operator variational inference · 2016
Later among the works it cites.
In Symposium on Advances in Approximate Bayesian Inference (AABI)
Vértes, E. and Sahani, M. (2016) Learning doubly intractable latent variable models via score matching · 2016
Later among the works it cites.
Journal of the Royal Statistical Society. Series B, (Statistical Methodology)
Dalalyan, A. S. (2017) Theoretical guarantees for approximate sampling from a smooth and log-concave density · 2017
Later among the works it cites.
Cambridge: Cambridge University Press
Ghosal, S. and van der Vaart, A. (2017) Fundamentals of nonparametric Bayesian inference · 2017
Later among the works it cites.
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In Advances in Neural Information Processing Systems
Fukumizu, K., Gretton, A., Schölkopf, B. and Sriperumbudur, B. K. (2008) Characteristic kernels on groups and semigroups · 2008
Cited alongside, same era.
Springer Publishing Company, Incorporated, 1st edn
Steinwart, I. and Christmann, A. (2008) Support vector machines · 2008
Cited alongside, same era.
Meyn, S., Tweedie, R. L. and Glynn, P. W. (2009) Markov chains and stochastic stability
2009
Cited alongside, same era.
John Wiley & Sons
Serfling, R. J. (2009) Approximation theorems of mathematical statistics · 2009
Cited alongside, same era.
Springer Berlin Heidelberg
Villani, C. (2009) Optimal transport: old and new · 2009
Cited alongside, same era.
In Advances in Neural Information Processing Systems
Christmann, A. and Steinwart, I. (2010) Universal kernels on non-standard input spaces · 2010
Cited alongside, same era.
— (2017) Measuring sample quality with kernels · 2017
Later among the works it cites.
In Advances in Neural Information Processing Systems
Jitkrittum, W., Xu, W., Szabo, Z., Fukumizu, K. and Gretton, A. (2017) A linear-time kernel goodness-of-fit test · 2017
Later among the works it cites.
Journal of the Royal Statistical Society: Series B (Statistical Methodology)
Oates, C. J., Girolami, M. and Chopin, N. (2017) Control functionals for Monte Carlo integration · 2017
Later among the works it cites.
Journal of the American Statistical Association
Schennach, S. M. and Wilhelm, D. (2017) A simple parametric model selection test · 2017
Later among the works it cites.
In Advances in Neural Information Processing Systems
Jitkrittum, W., Kanagawa, H., Sangkloy, P., Hays, J., Schölkopf, B. and Gretton, A. (2018) Informative features for model comparison · 2018
Later among the works it cites.
Journal of the American Statistical Association
Park, J. and Haran, M. (2018) Bayesian inference in the presence of intractable normalizing functions · 2018
Later among the works it cites.
In Proceedings of the 35th International Conference on Machine Learning
Yang, J., Liu, Q., Rao, V. and Neville, J. (2018) Goodness-of-fit testing for discrete distributions via Stein discrepancy · 2018
Later among the works it cites.
In Advances in Neural Information Processing Systems
Barp, A., Briol, F.-X., Duncan, A., Girolami, M. and Mackey, L. (2019) Minimum Stein discrepancy estimators · 2019
Closest in time.
Annals of Applied Probability
Bresler, G. and Nagaraj, D. (2019) Stein’s method for stationary distributions of Markov chains and application to Ising models · 2019
Closest in time.
In Proceedings of the 36th International Conference on Machine Learning, ICML
Chen, W. Y., Barp, A., Briol, F., Gorham, J., Girolami, M. A., Mackey, L. W. and Oates, C. J. (2019) Stein point Markov chain Monte Carlo · 2019
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Journal of Machine Learning Research
Dwivedi, R., Chen, Y., Wainwright, M. J. and Yu, B. (2019) Log-concave sampling: Metropolis-Hastings algorithms are fast · 2019
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Annals of Applied Probability
Gorham, J., Duncan, A. B., Vollmer, S. J. and Mackey, L. (2019) Measuring sample quality with diffusions · 2019
Closest in time.
Annals of the Institute of Statistical Mathematics
Henze, N. and Visagie, J. (2019) Testing for normality in any dimension based on a partial differential equation involving the moment generating function · 2019
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In Advances in Neural Information Processing Systems
Lim, J. N., Yamada, M., Schölkopf, B. and Jitkrittum, W. (2019) Kernel Stein tests for multiple model comparison · 2019
Closest in time.
Annals of Applied Probability
Reinert, G. and Ross, N. (2019) Approximating stationary distributions of fast mixing Glauber dynamics, with applications to exponential random graphs · 2019
Closest in time.
Journal of the American Statistical Association
Shao, S., Jacob, P. E., Ding, J. and Tarokh, V. (2019) Bayesian model comparison with the Hyvärinen score: computation and consistency · 2019
Closest in time.
Foundations and Trends® in Machine Learning
Borgwardt, K., Ghisu, E., Llinares-López, F., O’Bray, L. and Rieck, B. (2020) Graph kernels: State-of-the-art and future challenges · 2020
Closest in time.
The Annals of Applied Probability
Bou-Rabee, N., Eberle, A. and Zimmer, R. (2020) Coupling and convergence for Hamiltonian Monte Carlo · 2020
Closest in time.
Hodgkinson, L., Salomone, R. and Roosta, F. (2020) The reproducing Stein kernel approach for post-hoc corrected sampling
2020
Closest in time.
Journal of the Royal Statistical Society: Series B (Statistical Methodology)
Jacob, P. E., O’Leary, J. and Atchadé, Y. F. (2020) Unbiased Markov chain Monte Carlo methods with couplings · 2020
Closest in time.
In Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics
Xu, W. and Matsuda, T. (2020) A Stein goodness-of-fit test for directional distributions · 2020
Closest in time.
Annual Review of Statistics and Its Application
South, L. F., Riabiz, M., Teymur, O. and Oates, C. J. (2021) Postprocessing of MCMC · 2021
Closest in time.
Journal of the Royal Statistical Society Series B: Statistical Methodology
Matsubara, T., Knoblauch, J., Briol, F.-X. and Oates, C. J. (2022) Robust generalised Bayesian inference for intractable likelihoods · 2022
Closest in time.
Journal of the Royal Statistical Society Series B: Statistical Methodology
Riabiz, M., Chen, W. Y., Cockayne, J., Swietach, P., Niederer, S. A., Mackey, L. and Oates, C. J. (2022) Optimal thinning of MCMC output · 2022
Closest in time.
In Advances in Neural Information Processing Systems
Shi, J., Zhou, Y., Hwang, J., Titsias, M. K. and Mackey, L. (2022) Gradient estimation with discrete Stein operators · 2022
Closest in time.
Annals of Mathematical Statistics
Arvesen, J. N. (1969) Jackknifing U U -statistics · 2076
Closest in time.