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Name: ikki kishida
Type: User
Company: CodeNext
Location: Tokyo, Japan
Name: ikki kishida
Type: User
Company: CodeNext
Location: Tokyo, Japan
100 questions about NLP: http://www.cl.ecei.tohoku.ac.jp/nlp100/
Code for "Active One-shot Learning"
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/
A PyTorch implementation of the Transformer model in "Attention is All You Need".
Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning.
links of my implementation
ChainerCV: a Library for Deep Learning in Computer Vision
You can download all papers in cvpr2017 open access
detect duplicated pictures by features from deep network
Implementation of Densely Connected Convolutional Networks by chainer (Densely Connected Convolutional Networks: https://arxiv.org/abs/1608.06993)
A PyTorch Implementation for Densely Connected Convolutional Networks (DenseNets)
A PyTorch implementation of DenseNet.
get image from imagenet manually
dotfiles setting
A memory-efficient implementation of DenseNets
Deep Clustering for Unsupervised Learning of Visual Features
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
Implementation of FractalNet by chainer (FractalNet: Ultra-Deep Neural Networks without Residuals: https://arxiv.org/abs/1605.07648)
Implementation of gated convolutional networks by chainer (Language Modeling with Gated Convolutional Networks :https://arxiv.org/pdf/1612.08083v1.pdf)
Implementation of GoogLeNet by chainer (Going Deeper with Convolutions: https://arxiv.org/abs/1409.4842)
Implementation of googlenet-v2 by chainer (Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift: https://arxiv.org/abs/1502.03167)
Implementation of googlenet-v3 by chainer(Rethinking the Inception Architecture for Computer Vision :https://arxiv.org/abs/1512.00567)
Implementation of Highway Networks by chainer(Training Very Deep Networks :https://arxiv.org/abs/1507.06228)
ICCV 2019 Overcoming Catastrophic Forgetting with Unlabeled Data in the Wild
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.