104 Open source projects that are alternatives of or similar to Awesome Papers Fewshot

Collection of Reinforcement Learning / Meta Reinforcement Learning Environments.

awesome few shot / meta learning papers

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.

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

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

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

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

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

TensorFlow 2.0 implementation of MAML.

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

Python Meta-Feature Extractor package.

Code for the paper "Evolved Policy Gradients"

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

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

Meta Self-learning for Multi-Source Domain Adaptation： A Benchmark

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

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

Code for FOCAL Paper Published at ICLR 2021

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

Awesome Few-shot learning

Meta-DETR: Official PyTorch Implementation

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

No description or website provided.

Tools for generating mini-ImageNet dataset and processing batches

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

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

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

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

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.

Meta graph convolutional neural network-assisted resilient swarm communications

Official implementation of Meta-StyleSpeech and StyleSpeech

This repository implements the paper, Model-Agnostic Meta-Leanring for Fast Adaptation of Deep Networks.

One-Shot Learning with Triplet CNNs in Pytorch

Awesome Multitask Learning Resources

Code of Empirical Bayes Transductive Meta-Learning with Synthetic Gradients

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

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)

DropClass and DropAdapt - repository for the paper accepted to Speaker Odyssey 2020

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

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

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

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

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

Code for meta-learning initializations for image segmentation

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

Personalizing Dialogue Agents via Meta-Learning

LibFewShot: A Comprehensive Library for Few-shot Learning.

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

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

Implementation of "Make One-Shot Video Object Segmentation Efficient Again” and the semi-supervised fine-tuning "e-OSVOS" approach (NeurIPS 2020).

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

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

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

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

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

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..

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

Auto-tune the Entropy Temperature of Soft Actor-Critic via Metagradient - 7th ICML AutoML workshop 2020

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

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