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Code for the 'DARTS: Deceiving Autonomous Cars with Toxic Signs' paper
Interpretability and explainability of data and machine learning models
Project page for our paper: Interpreting Adversarially Trained Convolutional Neural Networks
This library augments road images to introduce various real world scenarios that pose challenges for training neural networks of Autonomous vehicles. Automold is created to train CNNs in specific weather and road conditions.
A curated list of awesome machine learning interpretability resources.
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
互联网首份程序员考公指南,由3位已经进入体制内的前大厂程序员联合献上。
This repository contains the implementation and the evaluation of our ESEC/FSE 2020 paper: Detecting Numerical Bugs in Neural Network Architectures.
Concolic Testing for Deep Neural Networks
DeepXplore code release
Code for the Proceedings of the National Academy of Sciences 2020 article, "Understanding the Role of Individual Units in a Deep Neural Network"
This repository contains our POC for a website which can easily check videos for manipulated areas. It was part of the Hackathon for Good in the Hague, 2019.
Code for MSc Thesis: Simulating Weather Conditions on Digital Images, uses a modified CycleGAN model to synthesize fog on clear images
Implementation of "Hybrid LSTM and Encoder-Decoder Architecture for Detection of Image Forgeries" paper.
The official Tensorflow implementation for ICCV'19 paper 'Attributing Fake Images to GANs: Learning and Analyzing GAN Fingerprints'
A scikit-learn compatible library for graph kernels
code for paper "Graph Structure of Neural Networks"
Implementation for the paper (CVPR Oral): High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks
[NeurIPS 2020] Semi-Supervision (Unlabeled Data) & Self-Supervision Improve Class-Imbalanced / Long-Tailed Learning
ManTra-Net: Manipulation Tracing Network For Detection And Localization of Image Forgeries With Anomalous Features
Models and examples built with TensorFlow
Code for the paper "Adversarial Training and Robustness for Multiple Perturbations", NeurIPS 2019
Codes for reproducing the experimental results in "Proper Network Interpretability Helps Adversarial Robustness in Classification", published at ICML 2020
Pytorch implementation of network design paradigm described in the paper "Designing Network Design Spaces"
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.