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KASPRZAK Mikolaj

Main Referenced Co-authors
Broderick, Tamara (3)
Campbell, Trevor (3)
Huggins, Jonathan (3)
PECCATI, Giovanni  (3)
DÖBLER, Christian  (2)
Main Referenced Disciplines
Mathematics (11)
Computer science (1)
Engineering, computing & technology: Multidisciplinary, general & others (1)

Publications (total 13)

The most downloaded
193 downloads
Huggins, J., Kasprzak, M., Campbell, T., & Broderick Tamara. (2020). Validated Variational Inference via Practical Posterior Error Bounds. Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS). https://hdl.handle.net/10993/41725

The most cited

13 citations (WOS)

Huggins, J., Kasprzak, M., Campbell, T., & Broderick Tamara. (2020). Validated Variational Inference via Practical Posterior Error Bounds. Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS). https://hdl.handle.net/10993/41725

Kasprzak, M., & Peccati, G. (October 2023). Vector-valued statistics of binomial processes: Berry-Esseen bounds in the convex distance. Annals of Applied Probability, 33 (5), 3449-3492. doi:10.1214/22-AAP1897
Peer reviewed

Döbler, C., Kasprzak, M., & Peccati, G. (February 2022). Functional Convergence of U-processes with Size-Dependent Kernels. Annals of Applied Probability, 32 (1), 551-601. doi:10.1214/21-AAP1688
Peer Reviewed verified by ORBi

Döbler, C., Kasprzak, M., & Peccati, G. (2022). The multivariate functional de Jong CLT. Probability Theory and Related Fields, 184 (1), 367-399. doi:10.1007/s00440-022-01114-3
Peer Reviewed verified by ORBi

Kasprzak, M., Giordano, R., & Broderick, T. (2022). How good is your Laplace approximation of the Bayesian posterior? Finite-sample computable error bounds for a variety of useful divergences. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/53906.

Wynne, G., Kasprzak, M., & Duncan, A. (2022). A Spectral Representation of Kernel Stein Discrepancy with Application to Goodness-of-Fit Tests for Measures on Infinite Dimensional Hilbert Spaces. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/53905.

Döbler, C., & Kasprzak, M. (2021). Stein's method of exchangeable pairs in multivariate functional approximations. Electronic Journal of Probability, 26, 1-50. doi:10.1214/21-EJP587
Peer Reviewed verified by ORBi

Kasprzak, M. (August 2020). Stein’s method for multivariate Brownian approximations of sums under dependence. Stochastic Processes and Their Applications, 130 (8), 4927-4967. doi:10.1016/j.spa.2020.02.006
Peer Reviewed verified by ORBi

Huggins, J., Kasprzak, M., Campbell, T., & Broderick Tamara. (2020). Validated Variational Inference via Practical Posterior Error Bounds. Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS).
Peer reviewed

Kasprzak, M. (2020). Functional approximations with Stein's method of exchangeable pairs. Annales Henri Poincare, 56 (4), 2540-564. doi:10.1214/20-AIHP1049
Peer reviewed

Huggins, J., Kasprzak, M., Campbell, T., & Broderick, T. (2019). Practical bounds on the error of Bayesian posterior approximations: A nonasymptotic approach. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/39831.

Huggins, J., Campbell, T., Kasprzak, M., & Broderick, T. (2019). Scalable Gaussian Process Inference with Finite-data Mean and Variance Guarantees. Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS) 2019.
Peer reviewed

Kasprzak, M. (2017). Diffusion approximations via Stein's method and time changes. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/39828.

Kasprzak, M., Duncan, A., & Vollmer, S. (2017). Note on A. Barbour’s paper on Stein’s method for diffusion approximations. Electronic Communications in Probability. doi:10.1214/17-ECP54
Peer Reviewed verified by ORBi

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