Ingmar Schuster

19 papers A* 2A 1Journal 14Unranked 1

Year	Rank	Type	Title / Venue / Authors
2021	A*	`conf`	Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting. ICML Kashif Rasul, Calvin Seward, Ingmar Schuster, Roland Vollgraf
2021	J	`jnl`	Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting. CoRR Kashif Rasul, Calvin Seward, Ingmar Schuster, Roland Vollgraf
2021	J	`jnl`	Feature space approximation for kernel-based supervised learning. Knowl. Based Syst. Patrick Gelß, Stefan Klus, Ingmar Schuster, Christof Schütte
2021	J	`jnl`	Markov Chain Importance Sampling - A Highly Efficient Estimator for MCMC. J. Comput. Graph. Stat. Ingmar Schuster, Ilja Klebanov
2021	A*	`conf`	Multivariate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows. ICLR Kashif Rasul, Abdul-Saboor Sheikh, Ingmar Schuster, Urs M. Bergmann, Roland Vollgraf
2020	J	`jnl`	A Rigorous Theory of Conditional Mean Embeddings. SIAM J. Math. Data Sci. Ilja Klebanov, Ingmar Schuster, Timothy John Sullivan
2020	J	`jnl`	Eigendecompositions of Transfer Operators in Reproducing Kernel Hilbert Spaces. J. Nonlinear Sci. Stefan Klus, Ingmar Schuster, Krikamol Muandet
2020	J	`jnl`	Feature space approximation for kernel-based supervised learning. CoRR Patrick Gelß, Stefan Klus, Ingmar Schuster, Christof Schütte
2020	A	`conf`	Kernel Conditional Density Operators. AISTATS Ingmar Schuster, Mattes Mollenhauer, Stefan Klus, Krikamol Muandet
2020	J	`jnl`	Multi-variate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows. CoRR Kashif Rasul, Abdul-Saboor Sheikh, Ingmar Schuster, Urs Bergmann, Roland Vollgraf
2019	J	`jnl`	Kernel Conditional Density Operators. CoRR Ingmar Schuster, Mattes Mollenhauer, Stefan Klus, Krikamol Muandet
2019	J	`jnl`	Set Flow: A Permutation Invariant Normalizing Flow. CoRR Kashif Rasul, Ingmar Schuster, Roland Vollgraf, Urs Bergmann
2018	J	`jnl`	A kernel-based approach to molecular conformation analysis. CoRR Stefan Klus, Andreas Bittracher, Ingmar Schuster, Christof Schütte
2018	J	`jnl`	Analyzing high-dimensional time-series data using kernel transfer operator eigenfunctions. CoRR Stefan Klus, Sebastian Peitz, Ingmar Schuster
2018	J	`jnl`	Markov Chain Importance Sampling - a highly efficient estimator for MCMC. CoRR Ingmar Schuster, Ilja Klebanov
2017	J	`jnl`	Eigendecompositions of Transfer Operators in Reproducing Kernel Hilbert Spaces. CoRR Stefan Klus, Ingmar Schuster, Krikamol Muandet
2017	—	`conf`	Kernel Sequential Monte Carlo. ECML/PKDD (1) Ingmar Schuster, Heiko Strathmann, Brooks Paige, Dino Sejdinovic
2016	—	`—`	Probabilistic models of natural language semantics Ingmar Schuster
2014	J	`jnl`	Bayesian factorization of joint categorical distributions for relational data and classical conditioning models. CoRR Ingmar Schuster, Patrick Jähnichen