| Validated Variational Inference via Practical Posterior Error Bounds JH Huggins, M Kasprzak, T Campbell, T Broderick arXiv preprint arXiv:1910.04102, 2019 | 68* | 2019 |
| Practical bounds on the error of Bayesian posterior approximations: A nonasymptotic approach JH Huggins, T Campbell, M Kasprzak, T Broderick arXiv preprint arXiv:1809.09505, 2018 | 39 | 2018 |
| Scalable Gaussian process inference with finite-data mean and variance guarantees JH Huggins, T Campbell, M Kasprzak, T Broderick The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 19 | 2019 |
| How good is your Laplace approximation of the Bayesian posterior? Finite-sample computable error bounds for a variety of useful divergences MJ Kasprzak, R Giordano, T Broderick arXiv preprint arXiv:2209.14992, 2022 | 18 | 2022 |
| Diffusion approximations via Stein's method and time changes MJ Kasprzak arXiv preprint arXiv:1701.07633, 2017 | 18 | 2017 |
| Stein’s method for multivariate Brownian approximations of sums under dependence MJ Kasprzak Stochastic Processes and their Applications 130 (8), 4927-4967, 2020 | 17 | 2020 |
| Functional approximations via Stein’s method of exchangeable pairs MJ Kasprzak Annales de l'Institut Henri Poincaré, Probabilités et Statistiques 56 (4 …, 2020 | 14* | 2020 |
| Note on A. Barbour’s paper on Stein’s method for diffusion approximations MJ Kasprzak, AB Duncan, SJ Vollmer | 14 | 2017 |
| A Fourier representation of kernel Stein discrepancy with application to Goodness-of-Fit tests for measures on infinite dimensional Hilbert spaces G Wynne, MJ Kasprzak, AB Duncan Bernoulli 31 (2), 868-893, 2025 | 12 | 2025 |
| Functional convergence of sequential U-processes with size-dependent kernels C Döbler, MJ Kasprzak, G Peccati The Annals of Applied Probability 32 (1), 551-601, 2022 | 12* | 2022 |
| Stein’s method of exchangeable pairs in multivariate functional approximations C Döbler, MJ Kasprzak Electronic Journal of Probability 26, 1-50, 2021 | 10 | 2021 |
| The multivariate functional de Jong CLT C Döbler, M Kasprzak, G Peccati Probability Theory and Related Fields 184 (1), 367-399, 2022 | 4 | 2022 |
| A targeted accuracy diagnostic for variational approximations Y Wang, M Kasprzak, JH Huggins International Conference on Artificial Intelligence and Statistics, 8351-8372, 2023 | 3 | 2023 |
| Vector-valued statistics of binomial processes: Berry–Esseen bounds in the convex distance MJ Kasprzak, G Peccati The Annals of Applied Probability 33 (5), 3449-3492, 2023 | 2 | 2023 |
| Quantitative Error Bounds for Scaling Limits of Stochastic Iterative Algorithms X Wang, MJ Kasprzak, J Negrea, S Bourguin, JH Huggins arXiv preprint arXiv:2501.12212, 2025 | | 2025 |
| Stein's method for functional approximations M Kasprzak University of Oxford, 2018 | | 2018 |
| Kernel Mean Embeddings for Functional Data Analysis G Wynne, AB Duncan, S Nagy, M Kasprzak Different Varimax Rotation Approaches of Functional PCA for the evolution of …, 0 | | |
Jonathan HugginsAssistant Professor of Statistics, Boston UniversityVerified email at bu.edu
