173 Open Source Meta Learning Software Projects
Free and open source meta learning code projects including engines, APIs, generators, and tools.
Maml Tensorflow17 ⭐
This repository implements the paper, Model-Agnostic Meta-Leanring for Fast Adaptation of Deep Networks.
PyTorch code for CVPR 2018 paper: Learning to Compare: Relation Network for Few-Shot Learning (Few-Shot Learning part)
Meta Critic Networks51 ⭐
Pytorch code for Arxiv Paper: Learning to learn: Meta-Critic Networks for Sample-Efficient Learning
Mt Net32 ⭐
Code accompanying the ICML-2018 paper "Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace"
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
MetaStyle: Three-Way Trade-Off Among Speed, Flexibility, and Quality in Neural Style Transfer
Pytorch Meta1543 ⭐
A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch
Learning To Learn By Pytorch40 ⭐
"Learning to learn by gradient descent by gradient descent "by PyTorch -- a simple re-implementation.
The code repository for "Few-Shot Learning via Embedding Adaptation with Set-to-Set Functions"
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..
The implementation of "Self-Supervised Generalisation with Meta Auxiliary Learning" [NeurIPS 2019].
Meta Transfer Learning538 ⭐
TensorFlow and PyTorch implementation of "Meta-Transfer Learning for Few-Shot Learning" (CVPR2019)
Hcn Prototypeloss Pytorch22 ⭐
Hierarchical Co-occurrence Network with Prototype Loss for Few-shot Learning (PyTorch)
Awesome Automl And Lightweight Models745 ⭐
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.
MetaPred: Meta-Learning for Clinical Risk Prediction with Limited Patient Electronic Health Records (KDD 2019)
Gnn Meta Attack108 ⭐
Implementation of the paper "Adversarial Attacks on Graph Neural Networks via Meta Learning".
Meta Learning Lstm Pytorch140 ⭐
pytorch implementation of Optimization as a Model for Few-shot Learning
Mtl Progress Github.io26 ⭐
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.
Learning to Learn how to Learn: Self-Adaptive Visual Navigation using Meta-Learning (https://arxiv.org/abs/1812.00971)
Combine multiple MNIST digits to create datasets with 100/1000 classes for few-shot learning/meta-learning
Implementation of our paper "Meta Reinforcement Learning with Task Embedding and Shared Policy"
The code for paper "CANet: Class-Agnostic Segmentation Networks with Iterative Refinement and Attentive Few-Shot Learning"
What I Have Read141 ⭐
Paper Lists, Notes and Slides, Focus on NLP. For summarization, please refer to https://github.com/xcfcode/Summarization-Papers
Few Shot Learning58 ⭐
Few-shot binary text classification with Induction Networks and Word2Vec weights initialization
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".
Meta Weight Net198 ⭐
NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).
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.
Deep Kernel Transfer142 ⭐
Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)
Maml Rl Tf216 ⭐
Implementation of Model-Agnostic Meta-Learning (MAML) applied on Reinforcement Learning problems in TensorFlow 2.
Pa Gnn17 ⭐
Implementation of paper "Transferring Robustness for Graph Neural Network Against Poisoning Attacks".
Cross-Domain Few-Shot Classification via Learned Feature-Wise Transformation (ICLR 2020 spotlight)
DropClass and DropAdapt - repository for the paper accepted to Speaker Odyssey 2020
Meta Blocks113 ⭐
A modular toolbox for meta-learning research with a focus on speed and reproducibility.
Cs330 Stanford 201932 ⭐
My notes and assignment solutions for Stanford CS330 (Fall 2019 & 2020) Deep Multi-Task and Meta Learning
PyTorch implementation of "An Ensemble of Epoch-wise Empirical Bayes for Few-shot Learning" (ECCV 2020)
Meta Interpolation71 ⭐
Source code for CVPR 2020 paper "Scene-Adaptive Video Frame Interpolation via Meta-Learning"
Metalearning4nlp Papers214 ⭐
A list of recent papers about Meta / few-shot learning methods applied in NLP areas.
Audioku Meta Transfer Learning40 ⭐
Implementation of meta-transfer-learning for ASR and LM (ACL 2020)
Repository containing code for the paper "Meta-Learning with Sparse Experience Replay for Lifelong Language Learning".
Source code for KDD 2020 paper "Meta-learning on Heterogeneous Information Networks for Cold-start Recommendation"
Awesome Real World Rl260 ⭐
Great resources for making Reinforcement Learning work in Real Life situations. Papers,projects and more.
[ECCV 2020] Scale Adaptive Network: Learning to Learn Parameterized Classification Networks for Scalable Input Images
Meta Sr56 ⭐
Pytorch implementation of Meta-Learning for Short Utterance Speaker Recognition with Imbalance Length Pairs (Interspeech, 2020)
[CVPR'17] Training a Correlation Filter end-to-end allows lightweight networks of 2 layers (600 kB) to high performance at fast speed..
Floodsung Meta Learning Papers2431 ⭐
Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning
This repo provides pytorch code which replicates the results of the Matching Networks for One Shot Learning paper on the Omniglot and MiniImageNet dataset