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We propose Pathfinder, a variational method for approximately sampling from differentiable log densities.
“Selecting the metric in hamiltonian monte carlo.”
Bales, B., Pourzanjani, A., Vehtari, A., and Petzold, L. (2019) · 1905
Earlier work this paper cites.
“Monte Carlo gradient estimation in machine learning.”
Mohamed, S., Rosca, M., Figurnov, M., and Mnih, A. (2019) · 1906
Earlier work this paper cites.
“A stochastic approximation method.”
Robbins, H. and Monro, S. (1951) · 1951
Earlier work this paper cites.
“The convergence of a class of double-rank minimization algorithms 1. General considerations.”
Broyden, C. G. (1970) · 1970
Earlier work this paper cites.
“A family of variable-metric methods derived by variational means.”
Goldfarb, D. (1970) · 1970
Earlier work this paper cites.
“Conditioning of quasi-Newton methods for function minimization.”
Shanno, D. F. (1970) · 1970
Earlier work this paper cites.
“Updating quasi-Newton matrices with limited storage.”
Nocedal, J. (1980) · 1980
Earlier work this paper cites.
“Estimation in parallel randomized experiments.”
Rubin, D. B. (1981) · 1981
Earlier work this paper cites.
Practical Methods of Optimization (Second Edition)
Fletcher, R. (1987) · 1987
Earlier work this paper cites.
“A noniterative sampling/importance resampling alternative to the data augmentation algorithm for creating a few imputations when fractions of missing information are modest: The SIR algorithm.”
— (1987) · 1987
Earlier work this paper cites.
“Some numerical experiments with variable-storage quasi-Newton algorithms.”
Gilbert, J. C. and Lemaréchal, C. (1989) · 1989
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.
“Representations of quasi-Newton matrices and their use in limited memory methods.”
Byrd, R. H., Nocedal, J., and Schnabel, R. B. (1994) · 1994
Earlier work this paper cites.
“A limited memory algorithm for bound constrained optimization.”
Byrd, R. H., Lu, P., Nocedal, J., and Zhu, C. (1995) · 1995
Earlier work this paper cites.
“Existence and uniqueness of monotone measure-preserving maps.”
McCann, R. J. (1995) · 1995
Earlier work this paper cites.
“Simulating ratios of normalizing constants via a simple identity: a theoretical exploration.”
Meng, X.-L. and Wong, W. H. (1996) · 1996
Earlier work this paper cites.
“Algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound-constrained optimization.”
Zhu, C., Byrd, R. H., Lu, P., and Nocedal, J. (1997) · 1997
Earlier work this paper cites.
“On MCMC sampling in Bayesian MLP neural networks.”
Vehtari, A., Sarkka, S., and Lampinen, J. (2000) · 2000
Earlier work this paper cites.
“Slice sampling.”
Neal, R. M. (2003) · 2003
Earlier work this paper cites.
“Non-centered parameterisations for hierarchical models and data augmentation.”
Papaspiliopoulos, O., Roberts, G. O., and Sköld, M. (2003) · 2003
Earlier work this paper cites.
“Practical Hilbert space approximate Bayesian Gaussian processes for probabilistic programming.”
Riutort-Mayol, G., Bürkner, P.-C., Andersen, M. R., Solin, A., and Vehtari, A. (2020) · 2004
Earlier work this paper cites.
“Fail fast [software debugging].”
Shore, J. (2004) · 2004
Cited alongside, same era.
“Truncated importance sampling.”
Ionides, E. L. (2008) · 2008
Cited alongside, same era.
Graphical Models, Exponential Families, and Variational Inference
Wainwright, M. J. and Jordan, M. I. (2008) · 2008
Cited alongside, same era.
“Robust, Accurate Stochastic Optimization for Variational Inference.”
Dhaka, A. K., Catalina, A., Andersen, M. R., Magnusson, M., Huggins, J. H., and Vehtari, A. (2020) · 2009
Cited alongside, same era.
Optimal Transport
Villani, C. (2009) · 2009
Cited alongside, same era.
“Particle Markov chain Monte Carlo methods.”
Andrieu, C., Doucet, A., and Holenstein, R. (2010) · 2010
Cited alongside, same era.
Dillon, J. V., Langmore, I., Tran, D., Brevdo, E., Vasudevan, S., Moore, D., Patton, B., Alemi, A., Hoffman, M., and Saurous, R. A. (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.
“Sparsity information and regularization in the horseshoe and other shrinkage priors.”
Piironen, J., Vehtari, A., et al. (2017) · 2017
Later among the works it cites.
“JAX: composable transformations of Python+NumPy programs.” URL http://github.com/google/jax
Bradbury, J., Frostig, R., Hawkins, P., Johnson, M. J., Leary, C., Maclaurin, D., Necula, G., Paszke, A., VanderPlas, J., Wanderman-Milne, S., and Zhang, Q. (2018) · 2018
Later among the works it cites.
“Turing: A language for flexible probabilistic inference.”
Ge, H., Xu, K., and Ghahramani, Z. (2018) · 2018
Later among the works it cites.
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Gelman, A., Vehtari, A., Simpson, D., Margossian, C. C., Carpenter, B., Yao, Y., Kennedy, L., Gabry, J., Bürkner, P.-C., and Modrák, M. (2020) · 2011
Cited alongside, same era.
Bayesian Data Analysis (Third Edition)
Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., and Rubin, D. B. (2013) · 2013
Cited alongside, same era.
“The no-U-turn sampler: Adaptively setting path lengths in Hamiltonian Monte Carlo.”
Hoffman, M. D. and Gelman, A. (2014) · 2014
Cited alongside, same era.
“Adam: A method for stochastic optimization.”
Kingma, D. P. and Ba, J. (2014) · 2014
Cited alongside, same era.
“Black Box Variational Inference.”
Ranganath, R., Gerrish, S., and Blei, D. (2014) · 2014
Cited alongside, same era.
“Hamiltonian Monte Carlo for hierarchical models.”
Betancourt, M. and Girolami, M. (2015) · 2015
Cited alongside, same era.
“Yes, but did it work?: Evaluating variational inference.”
Yao, Y., Vehtari, A., Simpson, D., and Gelman, A. (2018) · 2018
Later among the works it cites.
“Pyro: Deep universal probabilistic programming.”
Bingham, E., Chen, J. P., Jankowiak, M., Obermeyer, F., Pradhan, N., Karaletsos, T., Singh, R., Szerlip, P., Horsfall, P., and Goodman, N. D. (2019) · 2019
Later among the works it cites.
“Generalized multiple importance sampling.”
Elvira, V., Martino, L., Luengo, D., Bugallo, M. F., et al. (2019) · 2019
Later among the works it cites.
“Visualization in Bayesian workflow (with discussion).”
Gabry, J., Simpson, D., Vehtari, A., Betancourt, M., and Gelman, A. (2019) · 2019
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“Pareto smoothed importance sampling.”
Vehtari, A., Simpson, D., Gelman, A., Yao, Y., and Gabry, J. (2019) · 2019
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“Black-Box Variational Inference as a Parametric Approximation to Langevin Dynamics.”
Hoffman, M. and Ma, Y. (2020) · 2020
Later among the works it cites.
“Unbiased Markov chain Monte Carlo methods with couplings.”
Jacob, P. E., O’Leary, J., and Atchadé, Y. F. (2020) · 2020
Later among the works it cites.
transport: Computation of Optimal Transport Plans and Wasserstein Distances
Schuhmacher, D., Bähre, B., Gottschlich, C., Hartmann, V., Heinemann, F., and Schmitzer, B. (2020) · 2020
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“Hilbert space methods for reduced-rank Gaussian process regression.”
Solin, A. and Särkkä, S. (2020) · 2020
Later among the works it cites.
“SciPy 1.0: Fundamental algorithms for scientific computing in Python.”
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., et al. (2020) · 2020
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“Challenges and Opportunities in High-dimensional Variational Inference.”
Dhaka, A. K., Catalina, A., Welandawe, M., Andersen, M. R., Huggins, J., and Vehtari, A. (2021) · 2021
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“posteriordb: A database of Bayesian posterior inference.” URL https://github.com/stan-dev/posteriordb
Magnusson, M., Bürkner, P., and Vehtari, A. (2021) · 2021
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R: A Language and Environment for Statistical Computing
R Core Team (2021) · 2021
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“Invertible Flow Non Equilibrium sampling.”
Thin, A., Janati, Y., Corff, S. L., Ollion, C., Doucet, A., Durmus, A., Moulines, E., and Robert, C. (2021) · 2021
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“Rank-normalization, folding, and localization: An improved R ^ \widehat{R} for assessing convergence of MCMC.”
Vehtari, A., Gelman, A., Simpson, D., Carpenter, B., and Bürkner, P.-C. (2021) · 2021
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