Ingmar Schuster

According to our database, Ingmar Schuster authored at least 14 papers between 2014 and 2021.

Collaborative distances:

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

2021

Feature space approximation for kernel-based supervised learning.

Patrick Gelß, Stefan Klus, Ingmar Schuster, Christof Schütte

Knowl. Based Syst., 2021

Markov Chain Importance Sampling - A Highly Efficient Estimator for MCMC.

Ingmar Schuster, Ilja Klebanov

J. Comput. Graph. Stat., 2021

Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting.

Kashif Rasul, Calvin Seward, Ingmar Schuster, Roland Vollgraf

Proceedings of the 38th International Conference on Machine Learning, 2021

Multivariate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows.

Kashif Rasul, Abdul-Saboor Sheikh, Ingmar Schuster, Urs M. Bergmann, Roland Vollgraf

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

A Rigorous Theory of Conditional Mean Embeddings.

Ilja Klebanov, Ingmar Schuster, Timothy John Sullivan

SIAM J. Math. Data Sci., 2020

Eigendecompositions of Transfer Operators in Reproducing Kernel Hilbert Spaces.

Stefan Klus, Ingmar Schuster, Krikamol Muandet

J. Nonlinear Sci., 2020

Multi-variate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows.

Kashif Rasul, Abdul-Saboor Sheikh, Ingmar Schuster, Urs Bergmann, Roland Vollgraf

CoRR, 2020

Kernel Conditional Density Operators.

Ingmar Schuster, Mattes Mollenhauer, Stefan Klus, Krikamol Muandet

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

2019

Set Flow: A Permutation Invariant Normalizing Flow.

Kashif Rasul, Ingmar Schuster, Roland Vollgraf, Urs Bergmann

CoRR, 2019

2018

A kernel-based approach to molecular conformation analysis.

Stefan Klus, Andreas Bittracher, Ingmar Schuster, Christof Schütte

CoRR, 2018

Analyzing high-dimensional time-series data using kernel transfer operator eigenfunctions.

Stefan Klus, Sebastian Peitz, Ingmar Schuster

CoRR, 2018

2017

Kernel Sequential Monte Carlo.

Ingmar Schuster, Heiko Strathmann, Brooks Paige, Dino Sejdinovic

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

2016

Probabilistic models of natural language semantics

Ingmar Schuster

PhD thesis, 2016

2014

Bayesian factorization of joint categorical distributions for relational data and classical conditioning models.

Ingmar Schuster, Patrick Jähnichen

CoRR, 2014