Mikolaj J. Kasprzak

According to our database, Mikolaj J. Kasprzak authored at least 7 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Quantitative Error Bounds for Scaling Limits of Stochastic Iterative Algorithms.

Xiaoyu Wang, Mikolaj J. Kasprzak, Jeffrey Negrea, Solesne Bourguin, Jonathan H. Huggins

CoRR, January, 2025

How good is your Laplace approximation of the Bayesian posterior? Finite-sample computable error bounds for a variety of useful divergences.

Mikolaj J. Kasprzak, Ryan Giordano, Tamara Broderick

J. Mach. Learn. Res., 2025

2023

A Targeted Accuracy Diagnostic for Variational Approximations.

Yu Wang, Mikolaj J. Kasprzak, Jonathan H. Huggins

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2020

Validated Variational Inference via Practical Posterior Error Bounds.

Jonathan H. Huggins, Mikolaj J. Kasprzak, Trevor Campbell, Tamara Broderick

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Practical Posterior Error Bounds from Variational Objectives.

Jonathan H. Huggins, Mikolaj J. Kasprzak, Trevor Campbell, Tamara Broderick

CoRR, 2019

Scalable Gaussian Process Inference with Finite-data Mean and Variance Guarantees.

Jonathan H. Huggins, Trevor Campbell, Mikolaj J. Kasprzak, Tamara Broderick

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Practical bounds on the error of Bayesian posterior approximations: A nonasymptotic approach.

Jonathan H. Huggins, Trevor Campbell, Mikolaj J. Kasprzak, Tamara Broderick

CoRR, 2018