A Rigorous Theory of Conditional Mean Embeddings. - Ilja Klebanov; Ingmar Schuster; Timothy John Sullivan (SIAM J. Math. Data Sci., 2020)

Γ-convergence of Onsager-Machlup functionals. Part I: With applications to maximum a posteriori estimation in Bayesian inverse problems. - Birzhan Ayanbayev; Ilja Klebanov; Han Cheng Lie; Timothy John Sullivan (CoRR, 2021)

Γ-convergence of Onsager-Machlup functionals. Part II: Infinite product measures on Banach spaces. - Birzhan Ayanbayev; Ilja Klebanov; Han Cheng Lie; Timothy John Sullivan (CoRR, 2021)

Markov Chain Importance Sampling - A Highly Efficient Estimator for MCMC. - Ingmar Schuster; Ilja Klebanov (J. Comput. Graph. Stat., 2021)

Nonnegative matrix factorization for coherent set identification by direct low rank maximum likelihood estimation. - Robert Polzin; Ilja Klebanov; Nikolas Nüsken; Péter Koltai (CoRR, 2023)

Transporting Higher-Order Quadrature Rules: Quasi-Monte Carlo Points and Sparse Grids for Mixture Distributions. - Ilja Klebanov; Timothy John Sullivan (CoRR, 2023)

Deterministic Fokker-Planck Transport - With Applications to Sampling, Variational Inference, Kernel Mean Embeddings & Sequential Monte Carlo. - Ilja Klebanov (CoRR, 2024)

Lattice Rules Meet Kernel Cubature. - Vesa Kaarnioja; Ilja Klebanov; Claudia Schillings; Yuya Suzuki (CoRR, 2025)

Coherent Set Identification Via Direct Low Rank Maximum Likelihood Estimation. - Robert M. Polzin; Ilja Klebanov; Nikolas Nüsken; Péter Koltai (J. Nonlinear Sci., 2025)