1 code implementation • 19 Mar 2024 • Sebastian Bischoff, Alana Darcher, Michael Deistler, Richard Gao, Franziska Gerken, Manuel Gloeckler, Lisa Haxel, Jaivardhan Kapoor, Janne K Lappalainen, Jakob H Macke, Guy Moss, Matthijs Pals, Felix Pei, Rachel Rapp, A Erdem Sağtekin, Cornelius Schröder, Auguste Schulz, Zinovia Stefanidi, Shoji Toyota, Linda Ulmer, Julius Vetter
To demonstrate how these distances are used in practice, we evaluate generative models from different scientific domains, namely a model of decision making and a model generating medical images.
1 code implementation • 12 Feb 2024 • Julius Vetter, Guy Moss, Cornelius Schröder, Richard Gao, Jakob H. Macke
Scientific modeling applications often require estimating a distribution of parameters consistent with a dataset of observations - an inference task also known as source distribution estimation.
2 code implementations • 3 Dec 2023 • Guy Moss, Vjeran Višnjević, Olaf Eisen, Falk M. Oraschewski, Cornelius Schröder, Jakob H. Macke, Reinhard Drews
The geometry of ice shelves, and hence their buttressing strength, is determined by ice flow as well as by the local surface accumulation and basal melt rates, governed by atmospheric and oceanic conditions.
no code implementations • 24 May 2023 • Cornelius Schröder, Jakob H. Macke
We approach this problem in an amortized simulation-based inference framework: We define implicit model priors over a fixed set of candidate components and train neural networks to infer joint probability distributions over both, model components and associated parameters from simulations.
1 code implementation • NeurIPS 2020 • Cornelius Schröder, David Klindt, Sarah Strauss, Katrin Franke, Matthias Bethge, Thomas Euler, Philipp Berens
Here, we present a computational model of temporal processing in the inner retina, including inhibitory feedback circuits and realistic synaptic release mechanisms.
Ranked #1 on Blocking on ./01/01/1967
1 code implementation • NeurIPS 2019 • Cornelius Schröder, Ben James, Leon Lagnado, Philipp Berens
The inherent noise of neural systems makes it difficult to construct models which accurately capture experimental measurements of their activity.