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Name: WL
Type: User
Name: WL
Type: User
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Fast image augmentation library and easy to use wrapper around other libraries. Documentation: https://albumentations.ai/docs/
A collection of resources and papers on Diffusion Models
Awesome Knowledge-Distillation. 分类整理的知识蒸馏paper(2014-2021)。
PyTorch implementation of "Weight Uncertainty in Neural Networks"
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
This repository contains code for the paper "Decoupling Representation and Classifier for Long-Tailed Recognition", published at ICLR 2020
This is the implementation code for the paper "Trainable Undersampling for Class-Imbalance Learning" published in AAAI2019
Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch
Differentiable architecture search for convolutional and recurrent networks
Deep-Reinforcement-Learning-Hands-On-Second-Edition, published by Packt
PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....
Practical assignments of the Deep|Bayes summer school 2019
Implementation of Denoising Diffusion Probabilistic Model in Pytorch
Pytorch implementation for "Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets" (ECCV 2020 Spotlight)
Code for paper: DivideMix: Learning with Noisy Labels as Semi-supervised Learning
A Research-oriented Federated Learning Library. Supporting distributed computing, mobile/IoT on-device training, and standalone simulation. Best Paper Award at NeurIPS 2020 Federated Learning workshop. Join our Slack Community:(https://join.slack.com/t/fedml/shared_invite/zt-havwx1ee-a1xfOUrATNfc9DFqU~r34w)
A (PyTorch) imbalanced dataset sampler for oversampling low frequent classes and undersampling high frequent ones.
Bayesian Meta Sampling for Fast Uncertainty Adaptation
NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).
NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for class imbalance).
A new code framework that uses pytorch to implement meta-learning, and takes Meta-Weight-Net as an example.
Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.
PyTorch Implementation of Physics-informed Neural Networks
PyTorch for Deep Learning and Computer Vision Course
A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch
The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
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.