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A curated list of papers on disentangled representation learning inspired by https://github.com/sootlasten/disentangled-representation-papers and https://github.com/matthewvowels1/Awesome-VAEs.
The official codes of "Semi-supervised Models are Strong Unsupervised Domain Adaptation Learners".
implement for paper Rethinking Domain Adaptation Blending target Domain Adaptation by Adversarial Meta Adaptation Network
[ICLR2022] CDTrans: Cross-domain Transformer for Unsupervised Domain Adaptation
Improving Contrastive Learning by Visualizing Feature Transformation, ICCV 2021 Oral
Code for CoMatch: Semi-supervised Learning with Contrastive Graph Regularization
PyTorch implementation of "Emerging Disentanglement in Auto-Encoder Based Unsupervised Image Content Transfer"
pytorch implementation for Contrastive Adaptation Network
Repo for CReST: A Class-Rebalancing Self-Training Framework for Imbalanced Semi-Supervised Learning
Official code for "Towards Recognizing Unseen Categories in Unseen Domains"
[AAAI 21] Curriculum Labeling: Revisiting Pseudo-Labeling for Semi-Supervised Learning
Domain agnostic learning with disentangled representations
A PyTorch toolbox for domain adaptation and semi-supervised learning.
Torchreid: Deep learning person re-identification in PyTorch.
A collection of implementations of deep domain adaptation algorithms
Pytorch implementation of four neural network based domain adaptation techniques: DeepCORAL, DDC, CDAN and CDAN+E. Evaluated on benchmark dataset Office31.
Official pytorch implementation of "Feature Stylization and Domain-aware Contrastive Loss for Domain Generalization" ACMMM 2021 (Oral)
[ICLR2022] Code for "Learning Disentangled Representation by Exploiting Pretrained Generative Models: A Contrastive Learning View"
disentanglement_lib is an open-source library for research on learning disentangled representations.
This repository contains the full code for our paper "Theory and evaluation metrics for learning disentangled representations"
Implementation of 'DIVA: Domain Invariant Variational Autoencoders'
All about domain generalization
DomainBed is a suite to test domain generalization algorithms
Official implementation of PCS in essay "Prompt Vision Transformer for Domain Generalization"
Learning diverse image-to-image translation from unpaired data
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.