bethgelab Goto Github PK
Name: Bethge Lab
Type: Organization
Bio: Perceiving Neural Networks
Location: Tübingen
Blog: http://bethgelab.org
Name: Bethge Lab
Type: Organization
Bio: Perceiving Neural Networks
Location: Tübingen
Blog: http://bethgelab.org
NIPS Adversarial Vision Challenge
Adversarially Robust Neural Network on MNIST.
BWKI Task of the week
A challenge to explore adversarial robustness of neural networks on CIFAR10.
CiteME is a benchmark designed to test the abilities of language models in finding papers that are cited in scientific texts.
A method for training neural networks that are provably robust to adversarial attacks.
Code for the ICLR'24 paper: "Visual Data-Type Understanding does not emerge from Scaling Vision-Language Models"
Blind source separation based on the probabilistic tensor factorisation framework
Markerless tracking of user-defined features with deep learning
Information and scripts to run and develop the Bethge Lab Docker containers
Development of new unified docker container (WIP)
Docker Image with Jupyter for Deep Learning (Caffe, Theano, Lasagne, Keras)
Docker Image with Jupyter Notebook based on bethgelab/docker-xserver
Docker Image with Jupyter for Scientific Computing (Numpy, Scipy, Theano, Bokeh, etc.)
Docker Image with Jupyter for Scientific Computing (Numpy, Scipy)
Docker Image with Jupyter for Deep Learning including Torch
Docker Image with Xserver, OpenBLAS and correct user settings
A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX
Code for the paper: "No Zero-Shot Without Exponential Data: Pretraining Concept Frequency Determines Multimodal Model Performance"
Trained model weights, training and evaluation code from the paper "A simple way to make neural networks robust against diverse image corruptions"
Python package to corrupt arbitrary images.
Benchmarks introduced in the paper: "Lifelong Benchmarks: Efficient Model Evaluation in an Era of Rapid Progress"
Wrapper around Microsoft Academic Knowledge API to retrieve MAG data
Development of Mesos cluster
Fork of the MMDetection Toolbox containing the Robustness Benchmark from the paper "Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming" (merged)
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.