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Zero-variance control variates (ZV-CV) are a post-processing method to reduce the variance of Monte Carlo estimators of expectations using the derivatives of the log target.
Two models of double descent for weak features
Belkin, M., Hsu, D., and Xu, J. (2019) · 1903
Earlier work this paper cites.
Control variate selection for Monte Carlo integration
Leluc, R., Portier, F., and Segers, J. (2019) · 1906
Earlier work this paper cites.
South, L. F., Nemeth, C., and Oates, C. J. (2019a) · 1912
Earlier work this paper cites.
On relaxation-oscillations
Van der Pol, B. (1926) · 1926
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The generalized Weierstrass approximation theorem
Stone, M. H. (1948) · 1948
Earlier work this paper cites.
Equations of state calculations by fast computing machines
Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., and Teller, E. (1953) · 1953
Earlier work this paper cites.
Quadrature and interpolation formulas for tensor products of certain classes of functions
Smolyak, S. A. (1963) · 1963
Earlier work this paper cites.
Monte Carlo Methods
Hammersley, J. M. and Handscomb, D. C. (1964) · 1964
Earlier work this paper cites.
Ridge regression: Biased estimation for nonorthogonal problems
Hoerl, A. E. and Kennard, R. W. (1970) · 1970
Earlier work this paper cites.
A bound for the error in the normal approximation to the distribution of a sum of dependent random variables
Stein (1972) · 1972
Earlier work this paper cites.
Soft modeling by latent variables; the non-linear iterative partial least squares approach
Wold, H. (1975) · 1975
Earlier work this paper cites.
Hybrid Monte Carlo
Duane, S., Kennedy, A. D., Pendleton, B. J., and Roweth, D. (1987) · 1987
Earlier work this paper cites.
Stochastic Simulation
Ripley, B. (1987) · 1987
Earlier work this paper cites.
Analysis of hidden units in a layered network trained to classify sonar targets
Gorman, R. P. and Sejnowski, T. J. (1988) · 1988
Earlier work this paper cites.
Polygynie du cincle plongeur (cinclus cinclus) dans le côtes de Loraine
Marzolin, G. (1988) · 1988
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A Monte Carlo method for high dimensional integration
Ogata, Y. (1989) · 1989
Earlier work this paper cites.
Parallel tempering
Geyer, C. (1991) · 1991
Earlier work this paper cites.
Modeling survival and testing biological hypotheses using marked animals: a unified approach with case studies
Lebreton, J. D., Burnham, K. P., Clobert, J., and Anderson, D. R. (1992) · 1992
Earlier work this paper cites.
Regression shrinkage and selection via the lasso
Tibshirani, R. (1996) · 1996
Earlier work this paper cites.
Nonlinear approximation
DeVore, R. A. (1998) · 1998
Earlier work this paper cites.
Simulating normalising constants: from importance sampling to bridge sampling to path sampling
Gelman, A. and Meng, X.-L. (1998) · 1998
Earlier work this paper cites.
Log Gaussian Cox processes
Møller, J., Syversveen, A. R., and Waagepetersen, R. P. (1998) · 1998
Earlier work this paper cites.
Zero-variance principle for Monte Carlo algorithms
Assaraf, R. and Caffarel, M. (1999) · 1999
Earlier work this paper cites.
Bayesian animal survival estimation
Brooks, S. P., Catchpole, E. A., and Morgan, B. J. T. (2000) · 2000
Earlier work this paper cites.
Annealed importance sampling
Neal, R. M. (2001) · 2001
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A sequential particle filter method for static models
Chopin, N. (2002) · 2002
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Langevin diffusions and Metropolis-Hastings algorithms
Roberts, G. O. and Stramer, O. (2002) · 2002
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Monte Carlo methods in financial engineering
Glasserman, P. (2003) · 2003
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Least angle regression
Efron, B., Hastie, T., Johnstone, I., and Tibshirani, R. (2004) · 2004
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Regularization and variable selection via the elastic net
Zou, H. and Hastie, T. (2005) · 2005
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Sequential Monte Carlo samplers
Del Moral, P., Doucet, A., and Jasra, A. (2006) · 2006
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Measuring sample quality with Stein’s method
Gorham, J. and Mackey, L. (2015) · 2015
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Statistical Learning with Sparsity: The Lasso and Generalizations
Hastie, R., Tibshirani, R., and Wainwright, M. (2015) · 2015
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Towards automatic model comparison: An adaptive sequential Monte Carlo approach
Zhou, Y., Johansen, A. M., and Aston, J. A. D. (2015) · 2015
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Exploiting multi-core architectures for reduced-variance estimation with intractable likelihoods
Friel, N., Mira, A., and Oates, C. J. (2016) · 2016
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Particle approximations of the score and observed information matrix for parameter estimation in state-space models with linear computational cost
Nemeth, C., Fearnhead, P., and Mihaylova, L. (2016) · 2016
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On population-based simulation for static inference
Jasra, A., Stephens, D. A., and Holmes, C. C. (2007) · 2007
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Sure independence screening for ultrahigh dimensional feature space
Fan, J. and Lv, J. (2008) · 2008
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Marginal likelihood estimation via power posteriors
Friel, N. and Pettitt, A. N. (2008) · 2008
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A weakly informative default prior distribution for logistic and other regression models
Gelman, A., Jakulin, A., Pittau, M. G., and Su, Y.-S. (2008) · 2008
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Bayesian inference for differential equations
Girolami, M. (2008) · 2008
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Adaptively scaling the Metropolis Hastings algorithm using expected squared jumped distance
Pasarica, C. and Gelman, A. (2010) · 2010
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Oates, C. J., Papamarkou, T., and Girolami, M. (2016) · 2016
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Variance reduction via empirical variance minimization: convergence and complexity
Belomestny, D., Iosipoi, L., and Zhivotovskiy, N. (2017) · 2017
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On the sampling problem for kernel quadrature
Briol, F.-X., Oates, C. J., Cockayne, J., Chen, W. Y., and Girolami, M. (2017) · 2017
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Leave Pima Indians alone: binary regression as a benchmark for Bayesian computation
Chopin, N. and Ridgway, J. (2017) · 2017
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UCI machine learning repository
Dheeru, D. and Karra Taniskidou, E. (2017) · 2017
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Control functionals for Monte Carlo integration
Oates, C. J., Girolami, M., and Chopin, N. (2017) · 2017
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Adaptive tuning of Hamiltonian Monte Carlo within sequential Monte Carlo
Buchholz, A., Chopin, N., and Jacob, P. E. (2018) · 2018
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Approximation of Bayesian predictive p-values with regression ABC
Nott, D. J., Drovandi, C. C., Mengersen, K., and Evans, M. (2018) · 2018
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Unbiased and consistent nested sampling via sequential Monte Carlo
Salomone, R., South, L. F., Drovandi, C. C., and Kroese, D. P. (2018) · 2018
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ZVCV: Zero-Variance Control Variates
South, L. F. (2018) · 2018
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Regularised zero-variance control variates for high-dimensional variance reduction
South, L. F., Oates, C. J., Mira, A., and Drovandi, C. (2018) · 2018
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Message passing Stein variational gradient descent
Zhuo, J., Liu, C., Shi, J., Zhu, J., Chen, N., and Zhang, B. (2018) · 2018
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Control variates for stochastic gradient MCMC
Baker, J., Fearnhead, P., Fox, E. B., and Nemeth, C. (2019) · 2019
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Diffusion approximations and control variates for MCMC
Brosse, N., Durmus, A., Meyn, S., Éric Moulines, and Radhakrishnan, A. (2019) · 2019
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Unbiased Hamiltonian Monte Carlo with couplings
Heng, J. and Jacob, P. (2019) · 2019
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Convergence rates for a class of estimators based on Stein’s method
Oates, C. J., Cockayne, J., Briol, F. X., and Girolami, M. (2019) · 2019
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Monte Carlo integration with a growing number of control variates
Portier, F. and Segers, J. (2019) · 2019
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Neural control variates for variance reduction
Zhu, Z., Wan, R., and Zhong, M. (2019) · 2019
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A Riemann-Stein kernel method
Barp, A., Oates, C. J., Porcu, E., and Girolami, M. (2021) · 2021
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Scalable control variates for Monte Carlo methods via stochastic optimization
Si, S., Oates, C., Duncan, A. B., Carin, L., and Briol, F.-X. (2021) · 2021
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