queenie88 Goto Github PK
Name: queenie
Type: User
Name: queenie
Type: User
Source code for our AAAI paper "Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks".
Winning solution for the National Data Science Bowl competition on Kaggle (plankton classification)
Partial implemention of KCNet
A PyTorch implementation for exploring deep and shallow knowledge distillation (KD) experiments with flexibility
Implementations of knowledge distillation and knowledge transfer models in neural networks.
Code of Deep Kronecker-Product Matchingand Group-shuffiling Random Walk for Person Re-ID
Codes for AAAI2019 paper: Deep Neural Network Quantization via Layer-Wise Optimization using Limited Training Data
Implementation of our accepted CVPR 2018 paper "Rethinking Feature Distribution for Loss Functions in Image Classification"
L2G Auto-encoder: Understanding Point Clouds by Local-to-Global Reconstruction with Hierarchical Self-Attention
Label Embedding Network
Corrupted labels and label smoothing
Official Implementation of ICML 2019 Unsupervised label noise modeling and loss correction
Graph Neural Networks for Multi-Label Classification
Code for CVPR 2016 paper on Learning from Noisy Labels
方便学习的代码仓库
PyTorch Implementation of the paper Learning to Reweight Examples for Robust Deep Learning
Code for paper "Learning to Reweight Examples for Robust Deep Learning"
This is a complete package of recent deep learning methods for 3D point clouds in pytorch (with pretrained models).
Reproduction of "Learning to Learn by Gradient Descent by Gradient Descent"
PyTorch code for CVPR 2018 paper: Learning to Compare: Relation Network for Few-Shot Learning (Few-Shot Learning part)
PyTorch code for CVPR 2018 paper: Learning to Compare: Relation Network for Few-Shot Learning (Zero-Shot Learning part)
code for learning trajectory dependencies for human motion prediction
Light-Weight RefineNet for Real-Time Semantic Segmentation
Improving generalization by controlling label-noise information in neural network weights.
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.