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This is the reading list mainly on adversarial examples (attacks, defenses, etc.) I try to keep and update regularly.
A PyTorch implementation of the Transformer model in "Attention is All You Need".
A curated list of resources for Learning with Noisy Labels
CNNs for Sentence Classification in PyTorch
NeurIPS'18: Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels
This is an open source project (formerly named Listen, Attend and Spell - PyTorch Implementation) for end-to-end ASR implemented with Pytorch, the well known deep learning toolkit.
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
A very simple framework for state-of-the-art Natural Language Processing (NLP)
Implementation of Graph Convolutional Networks in TensorFlow
Deep Learning for humans
:book: Some language modeling tools for Keras
Google Chrome, Firefox, and Thunderbird extension that lets you write email in Markdown and render it before sending.
Adversarial Mahalanobis Distance-based Attentive Song Recommender for Automatic Playlist Continuation -- SIGIR 2019.
Exploring neural networks for collaborative filtering.
TensorFlow Neural Machine Translation Tutorial
Code Samples from Neural Networks for NLP
πThe Big-&-Extending-Repository-of-Transformers: Pretrained PyTorch models for Google's BERT, OpenAI GPT & GPT-2, Google/CMU Transformer-XL.
Papers about recommendation systems that I am interested in
Regularizing Matrix Factorization with User and Item Embeddings for Recommendation -- CIKM 2018
SDMR recommendation model -- WWW 2019
Sequence to Sequence Learning with Keras
Crafting adversarial images
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
Attempt at tracking states of the arts and recent results (bibliography) on speech recognition.
Python implementation of CBOW and skip-gram word vector models, and hierarchical softmax and negative sampling learning algorithms
A declarative, efficient, and flexible JavaScript library for building user interfaces.
π 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. πππ
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 β€οΈ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.