Resources

Code, tutorials, and other resources produced by the lab are available here.

Controversial Stimuli

This is a PyTorch tutorial on optimizing controversial stimuli for ImageNet classifiers, which demonstrates the method introduced in Golan, Raju, and Kriegeskorte (2020).

[Code on Github]

Ecoset

Ecoset is a collection of over 1.5 million images from 565 basic-level categories selected to better capture the distribution of objects relevant to humans, and provides an alternative to ILSVRC 2012 that is openly available for research purposes. It was introduced in Mehrer et al (2021) and developed in collaboration with the laboratory of Tim Kietzmann (corresponding author).

[Code/Dataset on Code Ocean]

Python Representational Similarity Analysis (rsatoolbox) toolbox

The rsatoolbox was developed by the labs of Nikolaus Kriegeskorte, Jörn Diedrichsen, Marieke Mur and Ian Charest. The toolbox replaces the 2013 matlab version the toolbox of rsatoolbox previously at ilogue/rsatoolbox and reflects many of the new methodological developments.

[link to toolbox]

Overview over subpackages and work flow in rsatoolbox

TorchLens

A new open-source Python package for extracting and characterizing hidden-layer activations in PyTorch models. This toolbox was developed by postdoctoral fellow JohnMark Taylor and detailed in his publication in Scientific Reports. 

[code on GitHub]

[visualizations for over 800 pre-trained DNNs]

[CoLab tutorial for TorchLens]

Example workflow for TorchLens