Ingmar Schuster

Publication Activity (10 Years)

Years Active: 2014-2021
Publications (10 Years): 17

Top Topics

Sequential Monte Carlo

Reproducing Kernel

Diffusion Models

Top Venues

SIAM J. Math. Data Sci.

J. Nonlinear Sci.

Publications

Kashif Rasul, Calvin Seward, Ingmar Schuster, Roland Vollgraf
Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting. ICML (2021)
Kashif Rasul, Calvin Seward, Ingmar Schuster, Roland Vollgraf
Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting. CoRR (2021)
Patrick Gelß, Stefan Klus, Ingmar Schuster, Christof Schütte
Feature space approximation for kernel-based supervised learning. Knowl. Based Syst. 221 (2021)
Ingmar Schuster, Ilja Klebanov
Markov Chain Importance Sampling - A Highly Efficient Estimator for MCMC. J. Comput. Graph. Stat. 30 (2) (2021)
Kashif Rasul, Abdul-Saboor Sheikh, Ingmar Schuster, Urs M. Bergmann, Roland Vollgraf
Multivariate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows. ICLR (2021)
Stefan Klus, Ingmar Schuster, Krikamol Muandet
Eigendecompositions of Transfer Operators in Reproducing Kernel Hilbert Spaces. J. Nonlinear Sci. 30 (1) (2020)
Ingmar Schuster, Mattes Mollenhauer, Stefan Klus, Krikamol Muandet
Kernel Conditional Density Operators. AISTATS (2020)
Kashif Rasul, Abdul-Saboor Sheikh, Ingmar Schuster, Urs Bergmann, Roland Vollgraf
Multi-variate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows. CoRR (2020)
Ilja Klebanov, Ingmar Schuster, Timothy John Sullivan
A Rigorous Theory of Conditional Mean Embeddings. SIAM J. Math. Data Sci. 2 (3) (2020)
Patrick Gelß, Stefan Klus, Ingmar Schuster, Christof Schütte
Feature space approximation for kernel-based supervised learning. CoRR (2020)
Ingmar Schuster, Mattes Mollenhauer, Stefan Klus, Krikamol Muandet
Kernel Conditional Density Operators. CoRR (2019)
Kashif Rasul, Ingmar Schuster, Roland Vollgraf, Urs Bergmann
Set Flow: A Permutation Invariant Normalizing Flow. CoRR (2019)
Stefan Klus, Sebastian Peitz, Ingmar Schuster
Analyzing high-dimensional time-series data using kernel transfer operator eigenfunctions. CoRR (2018)
Stefan Klus, Andreas Bittracher, Ingmar Schuster, Christof Schütte
A kernel-based approach to molecular conformation analysis. CoRR (2018)
Ingmar Schuster, Ilja Klebanov
Markov Chain Importance Sampling - a highly efficient estimator for MCMC. CoRR (2018)
Ingmar Schuster, Heiko Strathmann, Brooks Paige, Dino Sejdinovic
Kernel Sequential Monte Carlo. ECML/PKDD (1) (2017)
Stefan Klus, Ingmar Schuster, Krikamol Muandet
Eigendecompositions of Transfer Operators in Reproducing Kernel Hilbert Spaces. CoRR (2017)
Ingmar Schuster, Patrick Jähnichen
Bayesian factorization of joint categorical distributions for relational data and classical conditioning models. CoRR (2014)