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advances-in-label-noise-learning

A curated (most recent) list of resources for Learning with Noisy Labels

auto-6ml

Auto^6ML is a jittor library allowing users to achieve machine learning automation.

awesome-automl

A curated list of AutoML papers/tutorials/slides etc.

awesome-automl-and-lightweight-models

A list of high-quality (newest) AutoML works and lightweight models including 1.) Neural Architecture Search, 2.) Lightweight Structures, 3.) Model Compression, Quantization and Acceleration, 4.) Hyperparameter Optimization, 5.) Automated Feature Engineering.

awesome-knowledge-distillation

Awesome Knowledge-Distillation. 分类整理的知识蒸馏paper(2014-2021)。

awesome-learning-with-label-noise

A curated list of resources for Learning with Noisy Labels

awesome-meta-learning

A curated list of Meta-Learning resources/papers.

awesome-meta-learning-1

A curated list of Meta Learning papers, code, books, blogs, videos, datasets and other resources.

awesome-multimodal-ml

Reading list for research topics in multimodal machine learning

awesome-nas

A curated list of neural architecture search (NAS) resources.

awesome-zero-shot-learning

A curated list of papers, code and resources pertaining to zero shot learning

awsome-domain-adaptation

A collection of AWESOME things about domian adaptation

basic-multi-task-learning

This is a repository for Multi-task learning with toy data in Pytorch and Tensorflow

best-incremental-learning

An Incremental Learning, Continual Learning, and Life-Long Learning Repository

class-imbalance

Cost-Sensitive Learning / Resampling / SMOTE etc.

closerlookfewshot

source code to ICLR'19, 'A Closer Look at Few-shot Classification'

cmw-net

Pytorch implementation of TPAMI2023: CMW-NetCMW-Net: Learning a Class-Aware Sample Weighting Mapping for Robust Deep Learning

continual-learning

PyTorch implementation of various methods for continual learning (XdG, EWC, online EWC, SI, LwF, DGR, DGR+distill, RtF, iCaRL).

cost-sensitive-learning

coteaching_plus

ICML'19: How does Disagreement Help Generalization against Label Corruption?

dann

pytorch implementation of Domain-Adversarial Training of Neural Networks

deep-transfer-learning

A collection of implementations of deep domain adaptation algorithms

deep-value-networks-pytorch

Structured Prediction with Deep Value Networks (PyTorch implementation)

dirichlet_python

disentangled-representation-papers

A curated list of research papers related to learning disentangled representations

disentangling-vae

Experiments for understanding disentanglement in VAE latent representations

dividemix

Code for paper: DivideMix: Learning with Noisy Labels as Semi-supervised Learning

fast-autoaugment

Official Implementation of 'Fast AutoAugment' in PyTorch.

feat

The code repository for "Learning Embedding Adaptation for Few-Shot Learning"

feature_critic

Feature-Critic Networks for Heterogeneous Domain Generalisation