108 Open source projects that are alternatives of or similar to maml-tensorflow

Personalizing Dialogue Agents via Meta-Learning

My notes and assignment solutions for Stanford CS330 (Fall 2019 & 2020) Deep Multi-Task and Meta Learning

Implementation of Model-Agnostic Meta-Learning (MAML) applied on Reinforcement Learning problems in TensorFlow 2.

Code for meta-learning initializations for image segmentation

TensorFlow 2.0 implementation of MAML.

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

[CVPR2021] Meta Batch-Instance Normalization for Generalizable Person Re-Identification

Awesome Few-shot learning

Tools for building raster processing and display services

Implementation of our paper "Meta Reinforcement Learning with Task Embedding and Shared Policy"

Code for "One-Shot Visual Imitation Learning via Meta-Learning"

awesome few shot / meta learning papers

Repository to track the progress in Meta-Learning (MtL), including the datasets and the current state-of-the-art for the most common MtL problems.

Knowledge-Aware machine LEarning (KALE): accessible machine learning from multiple sources for interdisciplinary research, part of the 🔥PyTorch ecosystem

Pytorch implementation of Meta-Learning for Short Utterance Speaker Recognition with Imbalance Length Pairs (Interspeech, 2020)

Implementation of One Shot Learning using Convolutional Siamese Networks on Omniglot Dataset

Official implementation of Meta-StyleSpeech and StyleSpeech

MetaGenRL, a novel meta reinforcement learning algorithm. Unlike prior work, MetaGenRL can generalize to new environments that are entirely different from those used for meta-training.

The code repository for "Few-Shot Learning via Embedding Adaptation with Set-to-Set Functions"

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

[ECCV 2020] Scale Adaptive Network: Learning to Learn Parameterized Classification Networks for Scalable Input Images

Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning

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

Collection of Reinforcement Learning / Meta Reinforcement Learning Environments.

A classified list of meta learning papers based on realm.

ProMP: Proximal Meta-Policy Search

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

Python Meta-Feature Extractor package.

Official PyTorch implementation of "Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets" (ICLR 2021)

This is an official implementation for "Learning to Expand Audience via Meta Hybrid Experts and Critics for Recommendation and Advertising"(KDD2021).

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

Meta-Learning through Hebbian Plasticity in Random Networks: https://arxiv.org/abs/2007.02686

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

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

LibFewShot: A Comprehensive Library for Few-shot Learning.

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

Source code for ECCV2020 "Fast Adaptation to Super-Resolution Networks via Meta-Learning"

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

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

Great resources for making Reinforcement Learning work in Real Life situations. Papers,projects and more.

一些数据集处理相关的 API

Tools for generating mini-ImageNet dataset and processing batches

Source code for CVPR 2020 paper "Scene-Adaptive Video Frame Interpolation via Meta-Learning"

Code for the paper "Evolved Policy Gradients"

One-Shot Learning with Triplet CNNs in Pytorch

Python module to interface with OpenML

An efficient open-source AutoML system for automating machine learning lifecycle, including feature engineering, neural architecture search, and hyper-parameter tuning.

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

Code of Empirical Bayes Transductive Meta-Learning with Synthetic Gradients

Meta-Transfer Learning for Zero-Shot Super-Resolution (CVPR, 2020)

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

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)

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

a deep recurrent model for exchangeable data

Code for: "Learning To Adapt For Stereo" accepted at CVPR2019

Repository containing code for the paper "Meta-Learning with Sparse Experience Replay for Lifelong Language Learning".

Meta-DETR: Official PyTorch Implementation

Implementation for <Neural Similarity Learning> in NeurIPS'19.

Learning Meta Face Recognition in Unseen Domains, CVPR, Oral, 2020

Code for FOCAL Paper Published at ICLR 2021