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Name: Lyn
Type: User
Company: Osaka University
Bio: Researcher in AI
Location: Osaka
Name: Lyn
Type: User
Company: Osaka University
Bio: Researcher in AI
Location: Osaka
Code for "Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer"
Active Learning on Image Data using Bayesian ConvNets
Tensorflow implementation of "EGL-word" method in AAAI 2017 paper "Active Discriminative Text Representation Learning"
Active Decision Boundary Annotation with Deep Generative Models
Simple Tensorflow implementation of "Adaptive Gradient Methods with Dynamic Bound of Learning Rate" (ICLR 2019)
Chainer implementation of Auxiliary Deep Generative Models (ADGM) and Skip Deep Generative Model (SDGM)
This is a library dedicated to adversarial machine learning. Its purpose is to allow rapid crafting and analysis of attacks and defense methods for machine learning models. The Adversarial Robustness Toolbox provides an implementation for many state-of-the-art methods for attacking and defending classifiers. https://developer.ibm.com/code/open/projects/adversarial-robustness-toolbox/
[CVPR 2020] Code for paper "AdversarialNAS: Adversarial Neural Architecture Search for GANs".
The classical papers and codes about generative adversarial nets
Code for paper "Adversarial Generator-Encoder Networks" by Dmitry Ulyanov, Andrea Vedaldi and Victor Lempitsky
AI education materials for Chinese students, teachers and IT professionals.
All About the GANs(Generative Adversarial Networks) - Summarized lists for GAN
All Convolutional Network: (https://arxiv.org/abs/1412.6806#) implementation in Keras
Adversarially Robust Neural Network on MNIST.
Benchmarks of approximate nearest neighbor libraries in Python
Benchmarking approximate nearest neighbors
Torch implementations of various types of autoencoders
A curated list of awesome resources for adversarial examples in deep learning
A curated list of awesome adversarial machine learning resources
A list of high-quality (newest) AutoML works and lightweight models including 1.) Neural Architecture Search, 2.) Lightweight Structures, 3.) Model Compression & Acceleration, 4.) Hyperparameter Optimization, 5.) Automated Feature Engineering.
A curated list of resources dedicated to bayesian deep learning
📝Awesome and classical image retrieval papers
CVPR 论文收集,包含但不限于2020、2019、2018、2017文章
The most cited deep learning papers
Awesome Knowledge Distillation
机器学习资源大全中文版,包括机器学习领域的框架、库以及软件
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.