Publications and preprints
Publications and preprints
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Mikołaj J. Kasprzak, Ryan Giordano, Tamara Broderick: How good is your Laplace approximation of the Bayesian posterior? Finite-sample computable error bounds for a variety of useful divergences
Mikołaj J. Kasprzak, Ryan Giordano, Tamara Broderick: How good is your Laplace approximation of the Bayesian posterior? Finite-sample computable error bounds for a variety of useful divergences
arXiv:2209.14992, 2023+
George Wynne, Mikołaj J. Kasprzak, Andrew B. Duncan: A Fourier Representation of Kernel Stein Discrepancy with Application to Goodness-of-Fit Tests for Measures on Infinite Dimensional Hilbert Spaces
George Wynne, Mikołaj J. Kasprzak, Andrew B. Duncan: A Fourier Representation of Kernel Stein Discrepancy with Application to Goodness-of-Fit Tests for Measures on Infinite Dimensional Hilbert Spaces
Bernoulli (accepted), arXiv:2206.04552, 2023+
Yu Wang, Mikołaj J. Kasprzak, Jonathan H. Huggins: A Targeted Accuracy Diagnostic for Variational Approximations
Yu Wang, Mikołaj J. Kasprzak, Jonathan H. Huggins: A Targeted Accuracy Diagnostic for Variational Approximations
Proc. of the 26th International Conference on Artificial Intelligence and Statistics (AISTATS), arXiv:2302.12419, 2023
Mikołaj J. Kasprzak, Giovanni Peccati: Vector-valued statistics of binomial processes: Berry-Esseen bounds in the convex distance
Mikołaj J. Kasprzak, Giovanni Peccati: Vector-valued statistics of binomial processes: Berry-Esseen bounds in the convex distance
Annals of Applied Probability 33(5): 3449-3492, 2023, doi:10.1214/22-AAP1897, arXiv:2203.13137
Christian Döbler, Mikołaj J. Kasprzak, Giovanni Peccati: The multivariate functional de Jong CLT
Christian Döbler, Mikołaj J. Kasprzak, Giovanni Peccati: The multivariate functional de Jong CLT
Probability Theory and Related Fields, 184(1): 367-399, 2022, doi:10.1007/s00440-022-01114-3, arXiv:2104.01858
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