Fetching the paper…
Reading the bibliography…
Several researchers have proposed minimisation of maximum mean discrepancy (MMD) as a method to quantise probability measures, i.e., to approximate a target distribution by a representative point set.
Closed-form expressions for maximum mean discrepancy with applications to Wasserstein auto-encoders
Rustamov, R. M. (2019) · 1901
Earlier work this paper cites.
Statistical inference for generative models with maximum mean discrepancy
Briol, F.-X., Barp, A., Duncan, A. B., and Girolami, M. (2019a) · 1906
Earlier work this paper cites.
Theory of reproducing kernels
Aronszajn, N. (1950) · 1950
Earlier work this paper cites.
Gaussian measure in Hilbert space and applications in numerical analysis
Larkin, F. M. (1972) · 1972
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, C. (1972) · 1972
Earlier work this paper cites.
Density estimation for statistics and data analysis
Silverman, B. W. (1986) · 1986
Earlier work this paper cites.
Bayesian experimental design: a review
Chaloner, K. and Verdinelli, I. (1995) · 1995
Earlier work this paper cites.
Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming
Goemans, M. X. and Williamson, D. P. (1995) · 1995
Earlier work this paper cites.
Integral probability metrics and their generating classes of functions
Müller, A. (1997) · 1997
Earlier work this paper cites.
A generalized discrepancy and quadrature error bound
Hickernell, F. (1998) · 1998
Earlier work this paper cites.
A diffusion approach to Stein’s method on Riemannian manifolds
Le, H., Lewis, A., Bharath, K., and Fallaize, C. (2020) · 2003
Earlier work this paper cites.
A simplified local control model of calcium-induced calcium release in cardiac ventricular myocytes
Hinch, R., Greenstein, J., Tanskanen, A., Xu, L., and Winslow, R. (2004) · 2004
Earlier work this paper cites.
Optimal thinning of MCMC output
Riabiz, M., Chen, W., Cockayne, J., Swietach, P., Niederer, S. A., Mackey, L., and Oates, C. (2020) · 2005
Earlier work this paper cites.
Foundations of quantization for probability distributions
Graf, S. and Luschgy, H. (2007) · 2007
Earlier work this paper cites.
Tractability of Multivariate Problems: Standard information for functionals
Novak, E. and Woźniakowski, H. (2008) · 2008
Earlier work this paper cites.
Learning via Hilbert space embedding of distributions
Song, L. (2008) · 2008
Earlier work this paper cites.
Super-samples from kernel herding
Chen, Y., Welling, M., and Smola, A. (2010) · 2010
Earlier work this paper cites.
Digital nets and sequences: discrepancy theory and quasi–Monte Carlo integration
Dick, J. and Pillichshammer, F. (2010) · 2010
Cited alongside, same era.
Hilbert space embeddings and metrics on probability measures
Sriperumbudur, B. K., Gretton, A., Fukumizu, K., Schölkopf, B., and Lanckriet, G. R. (2010) · 2010
Cited alongside, same era.
On the equivalence between herding and conditional gradient algorithms
Bach, F., Lacoste-Julien, S., and Obozinski, G. (2012) · 2012
Cited alongside, same era.
Optimally-weighted herding is Bayesian quadrature
Huszár, F. and Duvenaud, D. (2012) · 2012
Cited alongside, same era.
Markov chains and stochastic stability
Meyn, S. P. and Tweedie, R. L. (2012) · 2012
Cited alongside, same era.
Equivalence of distance-based and RKHS-based statistics in hypothesis testing
Sejdinovic, D., Sriperumbudur, B., Gretton, A., and Fukumizu, K. (2013) · 2013
Stein points
Chen, W. Y., Mackey, L., Gorham, J., Briol, F.-X., and Oates, C. J. (2018) · 2018
Later among the works it cites.
Real analysis and probability
Dudley, R. M. (2018) · 2018
Later among the works it cites.
Support points
Mak, S., Joseph, V. R., et al. (2018) · 2018
Later among the works it cites.
Bayesian quadrature, energy minimization, and space-filling design
Pronzato, L. and Zhigljavsky, A. (2018) · 2018
Later among the works it cites.
Goodness-of-fit testing for discrete distributions via Stein discrepancy
Yang, J., Liu, Q., Rao, V., and Neville, J. (2018) · 2018
Later among the works it cites.
Maximum mean discrepancy gradient flow
Arbel, M., Korba, A., Salim, A., and Gretton, A. (2019) · 2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Frank-Wolfe Bayesian quadrature: Probabilistic integration with theoretical guarantees
Briol, F.-X., Oates, C., Girolami, M., and Osborne, M. A. (2015) · 2015
Cited alongside, same era.
Measuring sample quality with Stein’s method
Gorham, J. and Mackey, L. (2015) · 2015
Cited alongside, same era.
Sequential kernel herding: Frank-Wolfe optimization for particle filtering
Lacoste-Julien, S., Lindsten, F., and Bach, F. (2015) · 2015
Cited alongside, same era.
Super-sampling with a reservoir
Paige, B., Sejdinovic, D., and Wood, F. (2016) · 2016
Cited alongside, same era.
Semidefinite relaxations for partitioning, assignment and ordering problems
Rendl, F. (2016) · 2016
Cited alongside, same era.
On the equivalence between kernel quadrature rules and random feature expansions
Bach, F. (2017) · 2017
Cited alongside, same era.
Barp, A., Briol, F.-X., Duncan, A., Girolami, M., and Mackey, L. (2019) · 2019
Later among the works it cites.
Stein point Markov chain Monte Carlo
Chen, W. Y., Barp, A., Briol, F.-X., Gorham, J., Girolami, M., Mackey, L., and Oates, C. J. (2019) · 2019
Later among the works it cites.
Optimal Monte Carlo integration on closed manifolds
Ehler, M., Gräf, M., and Oates, C. J. (2019) · 2019
Later among the works it cites.
Measuring sample quality with diffusions
Gorham, J., Duncan, A., Mackey, L., and Vollmer, S. (2019) · 2019
Later among the works it cites.
Kernel-based and Bayesian methods for numerical integration
Karvonen, T. (2019) · 2019
Later among the works it cites.
Symmetry exploits for Bayesian cubature methods
Karvonen, T., Särkkä, S., and Oates, C. (2019) · 2019
Later among the works it cites.
MMD-Bayes: robust Bayesian estimation via maximum mean discrepancy
Chérief-Abdellatif, B.-E. and Alquier, P. (2020) · 2020
Closest in time.
Gurobi Optimizer Reference Manual
Gurobi Optimization, LLC (2020) · 2020
Closest in time.
The MOSEK Optimizer API for Python 9.2.26
MOSEK ApS (2020) · 2020
Closest in time.
Integer Programming: 2nd Edition
Wolsey, L. A. (2020) · 2020
Closest in time.
A Stein goodness-of-fit test for directional distributions
Xu, W. and Matsuda, T. (2020) · 2020
Closest in time.