104 Open source projects that are alternatives of or similar to Learn2learn

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

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

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

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

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.

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

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

Meta-Feature Extractor

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

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

Personalizing Dialogue Agents via Meta-Learning

One-Shot Learning with Triplet CNNs in Pytorch

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.

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

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

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

Collection for Few-shot Learning

Code for meta-learning initializations for image segmentation

Combine multiple MNIST digits to create datasets with 100/1000 classes for few-shot learning/meta-learning

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

Awesome Multitask Learning Resources

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

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

Official implementation of Meta-StyleSpeech and StyleSpeech

Meta graph convolutional neural network-assisted resilient swarm communications

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

Collection of Reinforcement Learning / Meta Reinforcement Learning Environments.

Repository for few-shot learning machine learning projects

No description or website provided.

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

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

Automated Machine Learning with scikit-learn

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

Graph meta learning via local subgraphs (NeurIPS 2020)

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

A dataset of datasets for learning to learn from few examples

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

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

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.

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-DETR: Official PyTorch Implementation

Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.

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

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

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

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

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

Python Meta-Feature Extractor package.

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

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

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

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

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

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

Memory efficient MAML using gradient checkpointing

Meta learning with BERT as a learner

Tensorflow Implementation of MAML

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

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