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    • Error Consistency with Confidence Intervals
      Jupyter Notebook
      MIT License
      0000Updated Nov 7, 2025Nov 7, 2025
    • Python implementation of psignifit, for psychometric function estimation
      Python
      Other
      266570Updated Jul 28, 2025Jul 28, 2025
    • psignifit

      Public
      Toolbox for Bayesian inference for psychometric functions
      MATLAB
      127500Updated Jan 4, 2025Jan 4, 2025
    • posters

      Public
      Here we share our posters and preprints, for example, for easy access on conferences.
      0000Updated Sep 16, 2024Sep 16, 2024
    • cblearn

      Public
      For reference, a fork of our ordinal embedding toolbox. For contributions, use the original repository.
      Python
      MIT License
      10000Updated Jun 12, 2024Jun 12, 2024
    • Python
      0200Updated May 9, 2024May 9, 2024
    • Python
      0600Updated May 9, 2024May 9, 2024
    • Psychophysical experiments with high luminance resolution in Python, using Psychopy and VPixx devices
      Python
      GNU Lesser General Public License v3.0
      55112Updated Mar 14, 2024Mar 14, 2024
    • Data and code from "Estimating the perceived dimension of psychophysical stimuli using triplet accuracy and hypothesis testing"
      Jupyter Notebook
      GNU General Public License v3.0
      1300Updated Jan 17, 2024Jan 17, 2024
    • Model as described in Schuett & Wichmann 2017
      MATLAB
      MIT License
      0500Updated Dec 18, 2022Dec 18, 2022
    • Error consistency: a black-box analysis for comparing errors between decision makers (NeurIPS 2020)
      R
      1900Updated Nov 23, 2022Nov 23, 2022
    • Code for "Trivial or impossible—dichotomous data difficulty masks model differences (on ImageNet and beyond)" (ICLR 2022)
      Jupyter Notebook
      0700Updated Mar 15, 2022Mar 15, 2022
    • In the team project summer term 2021, students are working on automating image manipulation using professional photography software.
      Lua
      MIT License
      1321Updated Nov 23, 2021Nov 23, 2021
    • Official repository for the paper "How Well do Feature Visualizations Support Causal Understanding of CNN Activations?".
      3000Updated Jul 28, 2021Jul 28, 2021
    • A script that applies the AdaIN style transfer method to arbitrary datasets
      Python
      Other
      38000Updated Jul 5, 2021Jul 5, 2021
    • Python
      2000Updated Jun 24, 2021Jun 24, 2021
    • Run CLIP inference on the ImageNet dataset and use these inferences as labels to train other models and again evaluate the trained model on Imagenet validation …
      Python
      BSD 3-Clause "New" or "Revised" License
      5000Updated Jun 21, 2021Jun 21, 2021
    • Benchmark your model on out-of-distribution datasets with carefully collected human comparison data
      Python
      54000Updated Jun 18, 2021Jun 18, 2021
    • bds

      Public
      Bayesian difference scaling. Statistical models for analyzing difference scaling experiments.
      Stan
      GNU General Public License v3.0
      1300Updated Apr 26, 2021Apr 26, 2021
    • Python package to corrupt arbitrary images.
      Python
      Apache License 2.0
      74000Updated Mar 31, 2021Mar 31, 2021
    • Figures & code from the paper "Shortcut Learning in Deep Neural Networks" (arXiv 2020)
      Python
      15000Updated Apr 21, 2020Apr 21, 2020
    • MATLAB
      0000Updated Mar 16, 2020Mar 16, 2020
    • Code, data and benchmark from the paper "Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming" (arXiv 2019)
      Jupyter Notebook
      MIT License
      24000Updated Jul 17, 2019Jul 17, 2019
    • Code to create Stylized-ImageNet, a stylized version of standard ImageNet (ICLR 2019 Oral)
      Python
      MIT License
      65100Updated May 2, 2019May 2, 2019
    • Pre-trained models, data, code & materials from the paper "ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustn…
      R
      107000Updated Apr 23, 2019Apr 23, 2019
    • Data, code & materials from the paper "Generalisation in humans and deep neural networks" (NeurIPS 2018)
      R
      Other
      22000Updated Aug 28, 2018Aug 28, 2018
    • Data and materials from the paper "Comparing deep neural networks against humans: object recognition when the signal gets weaker" (arXiv 2017)
      MATLAB
      Other
      16000Updated Oct 16, 2017Oct 16, 2017
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