156 Open source projects that are alternatives of or similar to Meta Learning Papers

FSL-Mate: A collection of resources for few-shot learning (FSL).

awesome few shot / meta learning papers

LibFewShot: A Comprehensive Library for Few-shot Learning.

Tensorflow implementation for paper: Learning to Compare: Relation Network for Few-Shot Learning.

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

Source codes for "Improved Few-Shot Visual Classification" (CVPR 2020), "Enhancing Few-Shot Image Classification with Unlabelled Examples" (WACV 2022), and "Beyond Simple Meta-Learning: Multi-Purpose Models for Multi-Domain, Active and Continual Few-Shot Learning" (Neural Networks 2022 - in submission)

Tensorflow Implementation of FaceNet: A Unified Embedding for Face Recognition and Clustering to find the celebrity whose face matches the closest to yours.

One-Shot Learning with Triplet CNNs in Pytorch

Personalizing Dialogue Agents via Meta-Learning

Code of Empirical Bayes Transductive Meta-Learning with Synthetic Gradients

Learning To Compare For Text , Few shot learning in text classification

PyTorch code for NeurIPSW 2020 paper (4th Workshop on Meta-Learning) "Few-Shot Unsupervised Continual Learning through Meta-Examples"

Official PyTorch implementation of "Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning" (ICCV2021 Oral)

Awesome Few-shot learning

Official repository of https://arxiv.org/abs/2111.04040v1

One-Shot Recognition of Manufacturing Defects in Steel Surfaces

Open-L2O: A Comprehensive and Reproducible Benchmark for Learning to Optimize Algorithms

[IJCAI 2021] Cross-Domain Few-Shot Classification via Adversarial Task Augmentation

Tensorflow Implementation of MAML

PyTorch Implementations For A Series Of Deep Learning-Based Recommendation Models (IN PROGRESS)

Few-shot binary text classification with Induction Networks and Word2Vec weights initialization

Meta-Feature Extractor

NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).

The source codes of the paper "Improving Few-shot Text Classification via Pretrained Language Representations" and "When Low Resource NLP Meets Unsupervised Language Model: Meta-pretraining Then Meta-learning for Few-shot Text Classification".

A resource list for causality in statistics, data science and physics

PyTorch code for CVPR 2018 paper: Learning to Compare: Relation Network for Few-Shot Learning (Few-Shot Learning part)

Codes and datasets for AAAI-2021 paper "Learning to Pre-train Graph Neural Networks"

Meta R-CNN : Towards General Solver for Instance-level Low-shot Learning

"Learning to learn by gradient descent by gradient descent "by PyTorch -- a simple re-implementation.

A list of recent papers about Meta / few-shot learning methods applied in NLP areas.

Code accompanying the ICML-2018 paper "Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace"

Bilevel Optimization Library in Python for Multi-Task and Meta Learning

Paper Lists, Notes and Slides, Focus on NLP. For summarization, please refer to https://github.com/xcfcode/Summarization-Papers

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.

A classified list of meta learning papers based on realm.

Hierarchical Co-occurrence Network with Prototype Loss for Few-shot Learning (PyTorch)

A modular toolbox for meta-learning research with a focus on speed and reproducibility.

Repository for few-shot learning machine learning projects

All materials you need for Federated Learning: blogs, videos, papers, and softwares, etc.

Automated Machine Learning with scikit-learn

The implementation of "Self-Supervised Generalisation with Meta Auxiliary Learning" [NeurIPS 2019].

[CVPR'17] Training a Correlation Filter end-to-end allows lightweight networks of 2 layers (600 kB) to high performance at fast speed..

A dataset of datasets for learning to learn from few examples

Cross-Domain Few-Shot Classification via Learned Feature-Wise Transformation (ICLR 2020 spotlight)

A hyperparameter optimization and data collection toolbox for convenient and fast prototyping of machine-learning models.

Learning to Learn how to Learn: Self-Adaptive Visual Navigation using Meta-Learning (https://arxiv.org/abs/1812.00971)

Implementation of the paper "Adversarial Attacks on Graph Neural Networks via Meta Learning".

Collection for Few-shot Learning

Reinforcement Learning Tutorial with Demo: DP (Policy and Value Iteration), Monte Carlo, TD Learning (SARSA, QLearning), Function Approximation, Policy Gradient, DQN, Imitation, Meta Learning, Papers, Courses, etc..

[ICLR'19] Meta-learning with differentiable closed-form solvers

TensorFlow and PyTorch implementation of "Meta-Transfer Learning for Few-Shot Learning" (CVPR2019)

Meta-Learning with Differentiable Convex Optimization (CVPR 2019 Oral)

The code for paper "CANet: Class-Agnostic Segmentation Networks with Iterative Refinement and Attentive Few-Shot Learning"

A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch

Awesome Multitask Learning Resources

This repo provides pytorch code which replicates the results of the Matching Networks for One Shot Learning paper on the Omniglot and MiniImageNet dataset

A PyTorch Library for Meta-learning Research

One-shot learning for image classification using Siamese neural networks

[CVPR '21] Official repository for Few-shot Image Generation via Cross-domain Correspondence

ProMP: Proximal Meta-Policy Search