Search Results for author: Sebastian Gerwinn

Found 9 papers, 2 papers with code

Estimation of Counterfactual Interventions under Uncertainties

no code implementations15 Sep 2023 Juliane Weilbach, Sebastian Gerwinn, Melih Kandemir, Martin Fraenzle

This ambiguity is particularly challenging in continuous settings in which a continuum of explanations exist for the same observation.

Validation of Composite Systems by Discrepancy Propagation

no code implementations21 Oct 2022 David Reeb, Kanil Patel, Karim Barsim, Martin Schiegg, Sebastian Gerwinn

Assessing the validity of a real-world system with respect to given quality criteria is a common yet costly task in industrial applications due to the vast number of required real-world tests.

Experimental Design

Inferring the Structure of Ordinary Differential Equations

no code implementations5 Jul 2021 Juliane Weilbach, Sebastian Gerwinn, Christian Weilbach, Melih Kandemir

Understanding physical phenomena oftentimes means understanding the underlying dynamical system that governs observational measurements.

regression Symbolic Regression

Learning Partially Known Stochastic Dynamics with Empirical PAC Bayes

no code implementations17 Jun 2020 Manuel Haussmann, Sebastian Gerwinn, Andreas Look, Barbara Rakitsch, Melih Kandemir

Neural Stochastic Differential Equations model a dynamical environment with neural nets assigned to their drift and diffusion terms.

Time Series Prediction

A joint maximum-entropy model for binary neural population patterns and continuous signals

no code implementations NeurIPS 2009 Sebastian Gerwinn, Philipp Berens, Matthias Bethge

Second-order maximum-entropy models have recently gained much interest for describing the statistics of binary spike trains.

Neurometric function analysis of population codes

no code implementations NeurIPS 2009 Philipp Berens, Sebastian Gerwinn, Alexander Ecker, Matthias Bethge

In this way, we provide a new rigorous framework for assessing the functional consequences of noise correlation structures for the representational accuracy of neural population codes that is in particular applicable to short-time population coding.

Bayesian estimation of orientation preference maps

no code implementations NeurIPS 2009 Sebastian Gerwinn, Leonard White, Matthias Kaschube, Matthias Bethge, Jakob H. Macke

Imaging techniques such as optical imaging of intrinsic signals, 2-photon calcium imaging and voltage sensitive dye imaging can be used to measure the functional organization of visual cortex across different spatial scales.

Gaussian Processes

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