Trained networks from "Interrogating theoretical models of neural computation with emergent property inference"
Year: 2021
Type: dataset
Abstract: In the manuscript "Interrogating theoretical models of neural computation with emergent property inference" by Bittner et al. 2021 https://www.biorxiv.org/content/10.1101/837567v3 , several deep neural networks were trained via EPI (and SNPE) to infer parameter distributions in mechanistic models. The parameters of these neural networks, optimization diagnostic information, and code to load these networks and generate all figures from the manuscript are provided in this zip file. All of the remaining software used in Bittner et al. 2021 can be found in this publicly available repository: https://github.com/cunningham-lab/epi
Authors: Bittner, Sean, Cunningham, John
Institution: Columbia University
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W4393416828