maml-rl-tf2Implementation of Model-Agnostic Meta-Learning (MAML) applied on Reinforcement Learning problems in TensorFlow 2.
Stars: ✭ 16 (-42.86%)
FOCAL-ICLRCode for FOCAL Paper Published at ICLR 2021
Stars: ✭ 35 (+25%)
Learning To Learn By Pytorch"Learning to learn by gradient descent by gradient descent "by PyTorch -- a simple re-implementation.
Stars: ✭ 31 (+10.71%)
Boml Bilevel Optimization Library in Python for Multi-Task and Meta Learning
Stars: ✭ 120 (+328.57%)
Awesome Automl And Lightweight ModelsA 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.
Stars: ✭ 691 (+2367.86%)
G MetaGraph meta learning via local subgraphs (NeurIPS 2020)
Stars: ✭ 50 (+78.57%)
KeitaMy personal toolkit for PyTorch development.
Stars: ✭ 124 (+342.86%)
LooperA resource list for causality in statistics, data science and physics
Stars: ✭ 23 (-17.86%)
PrompProMP: Proximal Meta-Policy Search
Stars: ✭ 181 (+546.43%)
MaxlThe implementation of "Self-Supervised Generalisation with Meta Auxiliary Learning" [NeurIPS 2019].
Stars: ✭ 101 (+260.71%)
Neural Process FamilyCode for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.
Stars: ✭ 53 (+89.29%)
CanetThe code for paper "CANet: Class-Agnostic Segmentation Networks with Iterative Refinement and Attentive Few-Shot Learning"
Stars: ✭ 135 (+382.14%)
L2p GnnCodes and datasets for AAAI-2021 paper "Learning to Pre-train Graph Neural Networks"
Stars: ✭ 48 (+71.43%)
Meta Learning PapersA classified list of meta learning papers based on realm.
Stars: ✭ 193 (+589.29%)
Mt NetCode accompanying the ICML-2018 paper "Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace"
Stars: ✭ 30 (+7.14%)
Metar CnnMeta R-CNN : Towards General Solver for Instance-level Low-shot Learning
Stars: ✭ 120 (+328.57%)
Learningtocompare fslPyTorch code for CVPR 2018 paper: Learning to Compare: Relation Network for Few-Shot Learning (Few-Shot Learning part)
Stars: ✭ 837 (+2889.29%)
Meta Learning PapersMeta Learning / Learning to Learn / One Shot Learning / Few Shot Learning
Stars: ✭ 2,420 (+8542.86%)
Cfnet[CVPR'17] Training a Correlation Filter end-to-end allows lightweight networks of 2 layers (600 kB) to high performance at fast speed..
Stars: ✭ 496 (+1671.43%)
Meta BlocksA modular toolbox for meta-learning research with a focus on speed and reproducibility.
Stars: ✭ 110 (+292.86%)
Meta Transfer LearningTensorFlow and PyTorch implementation of "Meta-Transfer Learning for Few-Shot Learning" (CVPR2019)
Stars: ✭ 439 (+1467.86%)
Metalearning4nlp PapersA list of recent papers about Meta / few-shot learning methods applied in NLP areas.
Stars: ✭ 163 (+482.14%)
TransferlearningTransfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
Stars: ✭ 8,481 (+30189.29%)
R2d2[ICLR'19] Meta-learning with differentiable closed-form solvers
Stars: ✭ 96 (+242.86%)
Meta-SACAuto-tune the Entropy Temperature of Soft Actor-Critic via Metagradient - 7th ICML AutoML workshop 2020
Stars: ✭ 19 (-32.14%)
SavnLearning to Learn how to Learn: Self-Adaptive Visual Navigation using Meta-Learning (https://arxiv.org/abs/1812.00971)
Stars: ✭ 135 (+382.14%)
Openml PythonPython module to interface with OpenML
Stars: ✭ 202 (+621.43%)
MultidigitmnistCombine multiple MNIST digits to create datasets with 100/1000 classes for few-shot learning/meta-learning
Stars: ✭ 48 (+71.43%)
MfrLearning Meta Face Recognition in Unseen Domains, CVPR, Oral, 2020
Stars: ✭ 127 (+353.57%)
Maml TfTensorflow Implementation of MAML
Stars: ✭ 44 (+57.14%)
Mini Imagenet ToolsTools for generating mini-ImageNet dataset and processing batches
Stars: ✭ 209 (+646.43%)
Few Shot Text ClassificationFew-shot binary text classification with Induction Networks and Word2Vec weights initialization
Stars: ✭ 32 (+14.29%)
MfeMeta-Feature Extractor
Stars: ✭ 20 (-28.57%)
HyperactiveA hyperparameter optimization and data collection toolbox for convenient and fast prototyping of machine-learning models.
Stars: ✭ 182 (+550%)
Hcn Prototypeloss PytorchHierarchical Co-occurrence Network with Prototype Loss for Few-shot Learning (PyTorch)
Stars: ✭ 17 (-39.29%)
MetarecPyTorch Implementations For A Series Of Deep Learning-Based Recommendation Models (IN PROGRESS)
Stars: ✭ 120 (+328.57%)
Few ShotRepository for few-shot learning machine learning projects
Stars: ✭ 727 (+2496.43%)
Awesome Real World RlGreat resources for making Reinforcement Learning work in Real Life situations. Papers,projects and more.
Stars: ✭ 234 (+735.71%)
Auto SklearnAutomated Machine Learning with scikit-learn
Stars: ✭ 5,916 (+21028.57%)
FewshotnlpThe 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".
Stars: ✭ 115 (+310.71%)
Meta DatasetA dataset of datasets for learning to learn from few examples
Stars: ✭ 483 (+1625%)
MzsrMeta-Transfer Learning for Zero-Shot Super-Resolution (CVPR, 2020)
Stars: ✭ 181 (+546.43%)
Reinforcement learning tutorial with demoReinforcement 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..
Stars: ✭ 442 (+1478.57%)
What I Have ReadPaper Lists, Notes and Slides, Focus on NLP. For summarization, please refer to https://github.com/xcfcode/Summarization-Papers
Stars: ✭ 110 (+292.86%)
MetaoptnetMeta-Learning with Differentiable Convex Optimization (CVPR 2019 Oral)
Stars: ✭ 412 (+1371.43%)
EpgCode for the paper "Evolved Policy Gradients"
Stars: ✭ 204 (+628.57%)
MatchingnetworksThis repo provides pytorch code which replicates the results of the Matching Networks for One Shot Learning paper on the Omniglot and MiniImageNet dataset
Stars: ✭ 256 (+814.29%)
Gnn Meta AttackImplementation of the paper "Adversarial Attacks on Graph Neural Networks via Meta Learning".
Stars: ✭ 99 (+253.57%)
e-osvosImplementation of "Make One-Shot Video Object Segmentation Efficient Again” and the semi-supervised fine-tuning "e-OSVOS" approach (NeurIPS 2020).
Stars: ✭ 31 (+10.71%)
Meta Weight NetNeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).
Stars: ✭ 158 (+464.29%)
Pytorch MetaA collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch
Stars: ✭ 1,239 (+4325%)
MilCode for "One-Shot Visual Imitation Learning via Meta-Learning"
Stars: ✭ 254 (+807.14%)
FeatThe code repository for "Few-Shot Learning via Embedding Adaptation with Set-to-Set Functions"
Stars: ✭ 229 (+717.86%)
CrossdomainfewshotCross-Domain Few-Shot Classification via Learned Feature-Wise Transformation (ICLR 2020 spotlight)
Stars: ✭ 204 (+628.57%)