2 citations · 2 across the 4 of their papers we have counts for
13 papers
Verifiable Regularity Criterion for Conditional Expectation Operators and Conditional Mean Embeddings with Applications to Nonparametric Regression, Bayesian Inverse Problems, and Koopman Operators
Maximiliano Hertel, Ilja Klebanov, Manuel Schaller +1
Conditional expectation operators (CEOs) and their associated conditional mean embeddings (CMEs) play a central role across applied mathematics and machine learning, appearing in n…
Error Bounds for Importance Sampling with Estimated Proposal Distributions
Cathrine Aeckerle-Willems, Ilja Klebanov, Simon Weissmann
Importance sampling with data-driven proposal distributions is widely used in practice. A common workflow first generates an auxiliary sample of size from an approximation of t…
Mixture-Weighted Ensemble Kalman Filter with Quasi-Monte Carlo Transport
Ilja Klebanov, Claudia Schillings, Dana Wrischnig
The Bootstrap Particle Filter (BPF) and the Ensemble Kalman Filter (EnKF) are two widely used methods for sequential Bayesian filtering: the BPF is asymptotically exact but can suf…
Lattice Rules Meet Kernel Cubature
Vesa Kaarnioja, Ilja Klebanov, Claudia Schillings +1
Rank-1 lattice rules are a class of equally weighted quasi-Monte Carlo methods that achieve essentially linear convergence rates for functions in a reproducing kernel Hilbert space…
Deterministic Fokker-Planck Transport -- With Applications to Sampling, Variational Inference, Kernel Mean Embeddings & Sequential Monte Carlo
Ilja Klebanov
The Fokker-Planck equation can be reformulated as a continuity equation, which naturally suggests using the associated velocity field in particle flow methods. While the resulting…
Transporting Higher-Order Quadrature Rules: Quasi-Monte Carlo Points and Sparse Grids for Mixture Distributions
Ilja Klebanov, T. J. Sullivan
Integration against, and hence sampling from, high-dimensional probability distributions is of essential importance in many application areas and has been an active research area f…