1 code implementation • 10 Apr 2024 • Marcel Nonnenmacher, Maneesh Sahani
The von Mises-Fisher distribution as an exponential family can be expressed in terms of either its natural or its mean parameters.
1 code implementation • NeurIPS Workshop DLDE 2021 • Marcel Nonnenmacher, David S. Greenberg
As a challenging test case, we train emulators on semi-implicit integration of 2D shallow-water equations with closed boundaries.
2 code implementations • 17 May 2019 • David S. Greenberg, Marcel Nonnenmacher, Jakob H. Macke
How can one perform Bayesian inference on stochastic simulators with intractable likelihoods?
no code implementations • NeurIPS 2017 • Marcel Nonnenmacher, Srinivas C. Turaga, Jakob H. Macke
Current approaches for dimensionality reduction on neural data are limited to single population recordings, and can not identify dynamics embedded across multiple measurements.
1 code implementation • NeurIPS 2017 • Jan-Matthis Lueckmann, Pedro J. Goncalves, Giacomo Bassetto, Kaan Öcal, Marcel Nonnenmacher, Jakob H. Macke
Our approach builds on recent advances in ABC by learning a neural network which maps features of the observed data to the posterior distribution over parameters.
1 code implementation • 29 Feb 2016 • Marcel Nonnenmacher, Christian Behrens, Philipp Berens, Matthias Bethge, Jakob H. Macke
Support for this notion has come from a series of studies which identified statistical signatures of criticality in the ensemble activity of retinal ganglion cells.
Neurons and Cognition