wichmann-lab Goto Github PK
Type: Organization
Type: Organization
Bayesian difference scaling. Statistical models for analyzing difference scaling experiments.
Official repository for the paper "How Well do Feature Visualizations Support Causal Understanding of CNN Activations?".
For reference, a fork of our ordinal embedding toolbox. For contributions, use the original repository.
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 dataset using original labels or CLIP labels
Error consistency: a black-box analysis for comparing errors between decision makers (NeurIPS 2020)
Data, code & materials from the paper "Generalisation in humans and deep neural networks" (NeurIPS 2018)
Python package to corrupt arbitrary images.
Benchmark your model on out-of-distribution datasets with carefully collected human comparison data
Data and materials from the paper "Comparing deep neural networks against humans: object recognition when the signal gets weaker" (arXiv 2017)
Here we share our posters and preprints, for example, for easy access on conferences.
Toolbox for Bayesian inference for psychometric functions
Psychophysical experiments with high luminance resolution in Python, using Psychopy and VPixx devices
Python clone of psignifit providing basic functionality
Code, data and benchmark from the paper "Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming" (arXiv 2019)
Data and code from "Estimating the perceived dimension of psychophysical stimuli using triplet accuracy and hypothesis testing"
Figures & code from the paper "Shortcut Learning in Deep Neural Networks" (arXiv 2020)
Model as described in Schuett & Wichmann 2017
A script that applies the AdaIN style transfer method to arbitrary datasets
Code to create Stylized-ImageNet, a stylized version of standard ImageNet (ICLR 2019 Oral)
In the team project summer term 2021, students are working on automating image manipulation using professional photography software.
Pre-trained models, data, code & materials from the paper "ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness" (ICLR 2019 Oral)
Code for "Trivial or impossible—dichotomous data difficulty masks model differences (on ImageNet and beyond)" (ICLR 2022)
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.