{"id":13408594,"url":"https://github.com/sudharsan13296/Awesome-Meta-Learning","last_synced_at":"2025-03-14T13:31:35.341Z","repository":{"id":42951461,"uuid":"191743342","full_name":"sudharsan13296/Awesome-Meta-Learning","owner":"sudharsan13296","description":" A curated list of Meta Learning papers, code, books, blogs, videos, datasets and other resources.","archived":false,"fork":false,"pushed_at":"2020-11-24T09:32:33.000Z","size":108,"stargazers_count":1471,"open_issues_count":1,"forks_count":298,"subscribers_count":69,"default_branch":"master","last_synced_at":"2024-05-19T21:14:05.375Z","etag":null,"topics":["deep-meta-learning","few-shot-learning","meta-reinforcement","metalearning","one-shot-learning","zero-shot-learning"],"latest_commit_sha":null,"homepage":null,"language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/sudharsan13296.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2019-06-13T10:38:04.000Z","updated_at":"2024-05-15T10:24:52.000Z","dependencies_parsed_at":"2022-08-30T05:31:47.427Z","dependency_job_id":null,"html_url":"https://github.com/sudharsan13296/Awesome-Meta-Learning","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sudharsan13296%2FAwesome-Meta-Learning","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sudharsan13296%2FAwesome-Meta-Learning/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sudharsan13296%2FAwesome-Meta-Learning/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sudharsan13296%2FAwesome-Meta-Learning/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/sudharsan13296","download_url":"https://codeload.github.com/sudharsan13296/Awesome-Meta-Learning/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243119546,"owners_count":20239321,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["deep-meta-learning","few-shot-learning","meta-reinforcement","metalearning","one-shot-learning","zero-shot-learning"],"created_at":"2024-07-30T20:00:53.917Z","updated_at":"2025-03-14T13:31:35.045Z","avatar_url":"https://github.com/sudharsan13296.png","language":null,"funding_links":[],"categories":["Uncategorized","Core Machine Learning Research","Others","Table of Contents","其他_机器学习与深度学习","Other Lists"],"sub_categories":["Uncategorized","Robustness, Interpretability, and Learning Paradigms","TeX Lists"],"readme":"# Awesome Meta Learning [![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)\n\nA curated list of Meta Learning papers, code, books, blogs, videos, datasets and other resources. \n\n# [Table of Contents]()\n\n* [Papers and Code](#Papers-and-Code)\n* [Books](#Books)\n* [Libraries](#Libraries)\n* [Blogs](#Blogs)\n* [Lecture Videos](#)\n* [Datasets](#Datasets)\n* [Workshops](#Workshops)\n* [Researchers](#Researchers)\n\n## Check out my Deep Reinforcement Learning Repo [here.](https://github.com/sudharsan13296/Deep-Reinforcement-Learning-With-Python)\n\n## [Papers and Code]()\n\nA curated set of papers along with code.\n\n\n### [Zero-Shot / One-Shot / Few-Shot / Low-Shot Learning]()\n\n* __Siamese Neural Networks for One-shot Image Recognition__, (2015), _Gregory Koch, Richard Zemel, Ruslan Salakhutdinov_. [[pdf]](https://www.cs.cmu.edu/~rsalakhu/papers/oneshot1.pdf) [[code]](https://github.com/sudharsan13296/Hands-On-Meta-Learning-With-Python/blob/master/02.%20Face%20and%20Audio%20Recognition%20using%20Siamese%20Networks/2.4%20Face%20Recognition%20Using%20Siamese%20Network.ipynb) \n\n* __Prototypical Networks for Few-shot Learning__, (2017), _Jake Snell, Kevin Swersky, Richard S. Zemel_. [[pdf]](https://arxiv.org/pdf/1703.05175.pdf) [[code]](https://github.com/sudharsan13296/Hands-On-Meta-Learning-With-Python/blob/master/03.%20Prototypical%20Networks%20and%20its%20Variants/3.3%20Omniglot%20Character%20set%20classification%20using%20Prototypical%20Network.ipynb)\n\n* __Gaussian Prototypical Networks for Few-Shot Learning on Omniglot__ (2017), _Stanislav Fort_. [[pdf]](https://arxiv.org/pdf/1708.02735.pdf) [[code]](https://github.com/stanislavfort/gaussian-prototypical-networks) \n\n* __Matching Networks for One Shot Learning__, (2017), _Oriol Vinyals, Charles Blundell, Timothy Lillicrap, Koray Kavukcuoglu, Daan Wierstra_. [[pdf]](https://arxiv.org/pdf/1606.04080.pdf) [[code]](https://github.com/sudharsan13296/Hands-On-Meta-Learning-With-Python/blob/master/04.%20Relation%20and%20Matching%20Networks%20Using%20Tensorflow/4.9%20Matching%20Networks%20Using%20Tensorflow.ipynb) \n\n* __Learning to Compare: Relation Network for Few-Shot Learning__, (2017), _Flood Sung, Yongxin Yang, Li Zhang, Tao Xiang, Philip H.S. Torr, Timothy M. Hospedales_. [[pdf]](https://arxiv.org/pdf/1711.06025.pdf) [[code]](https://github.com/sudharsan13296/Hands-On-Meta-Learning-With-Python/blob/master/04.%20Relation%20and%20Matching%20Networks%20Using%20Tensorflow/4.5%20Building%20Relation%20Network%20Using%20Tensorflow.ipynb)\n\n* __One-shot Learning with Memory-Augmented Neural Networks__, (2016), _Adam Santoro, Sergey Bartunov, Matthew Botvinick, Daan Wierstra, Timothy Lillicrap_. [[pdf]](https://arxiv.org/pdf/1605.06065.pdf) [[code]](https://github.com/vineetjain96/one-shot-mann)\n\n* __Optimization as a Model for Few-Shot Learning__, (2016), _Sachin Ravi and Hugo Larochelle_. [[pdf]](https://openreview.net/pdf?id=rJY0-Kcll) [[code]](https://github.com/gitabcworld/FewShotLearning)\n\n* __An embarrassingly simple approach to zero-shot learning__, (2015), _B Romera-Paredes, Philip H. S. Torr_. [[pdf]](http://proceedings.mlr.press/v37/romera-paredes15.pdf) [[code]](https://github.com/bernard24/Embarrassingly-simple-ZSL)\n\n* __Low-shot Learning by Shrinking and Hallucinating Features__, (2017), _Bharath Hariharan, Ross Girshick_.  [[pdf]](https://arxiv.org/pdf/1606.02819.pdf) [[code]](https://github.com/facebookresearch/low-shot-shrink-hallucinate)\n\n* __Low-shot learning with large-scale diffusion__, (2018), _Matthijs Douze, Arthur Szlam, Bharath Hariharan, Hervé Jégou_. \n[[pdf]](https://arxiv.org/pdf/1706.02332v2.pdf) [[code]](https://github.com/facebookresearch/low-shot-with-diffusion)\n\n* __Low-Shot Learning with Imprinted Weights__, (2018), _Hang Qi, Matthew Brown, David G. Lowe_. [[pdf]](http://openaccess.thecvf.com/content_cvpr_2018/papers/Qi_Low-Shot_Learning_With_CVPR_2018_paper.pdf) [[code]](https://github.com/YU1ut/imprinted-weights) \n\n\n* __One-Shot Video Object Segmentation__, (2017), _S. Caelles and K.K. Maninis and J. Pont-Tuset and L. Leal-Taixe' and D. Cremers and L. Van Gool_. [[pdf]](http://vision.ee.ethz.ch/~cvlsegmentation/osvos/) [[code]](https://github.com/scaelles/OSVOS-TensorFlow)\n\n* __One-Shot Learning for Semantic Segmentation__, (2017), _Amirreza Shaban, Shray Bansal, Zhen Liu, Irfan Essa, Byron Boots_. [[pdf]](https://arxiv.org/abs/1709.03410) [[code]](https://github.com/lzzcd001/OSLSM)\n\n* __Few-Shot Segmentation Propagation with Guided Networks__, (2018), _Kate Rakelly, Evan Shelhamer, Trevor Darrell, Alexei A. Efros, Sergey Levine_. [[pdf]](https://arxiv.org/abs/1806.07373) [[code]](https://github.com/shelhamer/revolver)\n\n* __Few-Shot Semantic Segmentation with Prototype Learning__, (2018), _Nanqing Dong and Eric P. Xing_. [[pdf]](http://bmvc2018.org/contents/papers/0255.pdf)\n\n* __Dynamic Few-Shot Visual Learning without Forgetting__, (2018), _Spyros Gidaris, Nikos Komodakis_. [[pdf]](https://arxiv.org/pdf/1804.09458.pdf) [[code]](https://github.com/gidariss/FewShotWithoutForgetting)\n\n* __Feature Generating Networks for Zero-Shot Learning__, (2017), _Yongqin Xian, Tobias Lorenz, Bernt Schiele, Zeynep Akata_. [[pdf]](https://arxiv.org/pdf/1712.00981.pdf)\n\n* __Meta-Learning Deep Visual Words for Fast Video Object Segmentation__, (2019), _Harkirat Singh Behl, Mohammad Najafi, Anurag Arnab, Philip H.S. Torr_. [[pdf]](https://arxiv.org/pdf/1812.01397.pdf)\n\n\n## [Model Agnostic Meta Learning]()\n\n* __Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks__, (2017), _Chelsea Finn, Pieter Abbeel, Sergey Levine_. [[pdf]](https://arxiv.org/pdf/1703.03400.pdf) [[code]](https://github.com/sudharsan13296/Hands-On-Meta-Learning-With-Python/blob/master/06.%20MAML%20and%20it's%20Variants/6.5%20Building%20MAML%20From%20Scratch.ipynb)\n\n* __Adversarial Meta-Learning__, (2018), _Chengxiang Yin, Jian Tang, Zhiyuan Xu, Yanzhi Wang_. [[pdf]](https://arxiv.org/pdf/1806.03316.pdf) [[code]](https://github.com/sudharsan13296/Hands-On-Meta-Learning-With-Python/blob/master/06.%20MAML%20and%20it's%20Variants/6.7%20Building%20ADML%20From%20Scratch.ipynb)\n\n* __On First-Order Meta-Learning Algorithms__, (2018), _Alex Nichol, Joshua Achiam, John Schulman_. [[pdf]](https://arxiv.org/pdf/1803.02999.pdf) [[code]](https://github.com/sudharsan13296/Hands-On-Meta-Learning-With-Python/blob/master/07.%20Meta-SGD%20and%20Reptile%20Algorithms/7.7%20Sine%20wave%20Regression%20Using%20Reptile.ipynb)\n\n* __Meta-SGD: Learning to Learn Quickly for Few-Shot Learning__, (2017), _Zhenguo Li, Fengwei Zhou, Fei Chen, Hang Li_. [[pdf]](https://arxiv.org/pdf/1707.09835.pdf) [[code]](https://github.com/sudharsan13296/Hands-On-Meta-Learning-With-Python/blob/master/07.%20Meta-SGD%20and%20Reptile%20Algorithms/7.4%20Building%20Meta-SGD%20from%20Scratch.ipynb) \n\n* __Gradient Agreement as an Optimization Objective for Meta-Learning__, (2018), _Amir Erfan Eshratifar, David Eigen, Massoud Pedram_. [[pdf]](https://arxiv.org/pdf/1810.08178.pdf) [[code]](https://github.com/sudharsan13296/Hands-On-Meta-Learning-With-Python/blob/master/08.%20Gradient%20Agreement%20As%20An%20Optimization%20Objective/8.4%20Building%20Gradient%20Agreement%20Algorithm%20with%20MAML.ipynb)\n\n* __Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace__, (2018), _Yoonho Lee, Seungjin Choi_. [[pdf]](https://arxiv.org/pdf/1801.05558.pdf) [[code]](https://github.com/yoonholee/MT-net)\n\n* __A Simple Neural Attentive Meta-Learner__, (2018), _Nikhil Mishra, Mostafa Rohaninejad, Xi Chen, Pieter Abbeel_. [[pdf]](https://arxiv.org/pdf/1707.03141.pdf) [[code]](https://github.com/eambutu/snail-pytorch)\n\n* __Personalizing Dialogue Agents via Meta-Learning__, (2019), _Zhaojiang Lin, Andrea Madotto, Chien-Sheng Wu, Pascale Fung_. [[pdf]](https://arxiv.org/pdf/1905.10033.pdf) [[code]](https://github.com/HLTCHKUST/PAML) \n\n* __How to train your MAML__, (2019), _Antreas Antoniou, Harrison Edwards, Amos Storkey_. [[pdf]](https://arxiv.org/pdf/1810.09502.pdf) [[code]](https://github.com/AntreasAntoniou/HowToTrainYourMAMLPytorch)\n\n* __Learning to learn by gradient descent by gradient descent__, (206), _Marcin Andrychowicz, Misha Denil, Sergio Gomez, Matthew W. Hoffman, David Pfau, Tom Schaul, Brendan Shillingford, Nando de Freitas_. [[pdf]](https://arxiv.org/pdf/1606.04474.pdf) [[code]](https://github.com/deepmind/learning-to-learn)\n\n* __Unsupervised Learning via Meta-Learning__, (2019), _Kyle Hsu, Sergey Levine, Chelsea Finn_. [[pdf]](https://arxiv.org/pdf/1810.02334.pdf) [[code]](https://github.com/hsukyle/cactus-maml)\n\n\n* __Few-Shot Image Recognition by Predicting Parameters from Activations__, (2018), _Siyuan Qiao, Chenxi Liu, Wei Shen, Alan Yuille_. [[pdf]](https://arxiv.org/pdf/1706.03466.pdf) [[code]](https://github.com/joe-siyuan-qiao/FewShot-CVPR)\n\n\n* __One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning__, (2018), _Tianhe Yu, Chelsea Finn, Annie Xie, Sudeep Dasari, Pieter Abbeel, Sergey Levine_, [[pdf]](https://arxiv.org/pdf/1802.01557.pdf) [[code]](https://github.com/aravind0706/upn)\n\n* __MetaGAN: An Adversarial Approach to Few-Shot Learning__, (2018), _ZHANG, Ruixiang and Che, Tong and Ghahramani, Zoubin and Bengio, Yoshua and Song, Yangqiu_. [[pdf]](http://papers.nips.cc/paper/7504-metagan-an-adversarial-approach-to-few-shot-learning.pdf) \n\n* __Fast Parameter Adaptation for Few-shot Image Captioning and Visual Question Answering__,(2018), _Xuanyi Dong, Linchao Zhu, De Zhang, Yi Yang, Fei Wu_. [[pdf]](https://xuanyidong.com/pdf/FPAIT-MM-18.pdf) \n\n* __CAML: Fast Context Adaptation via Meta-Learning__, (2019), _Luisa M Zintgraf, Kyriacos Shiarlis, Vitaly Kurin, Katja Hofmann, Shimon Whiteson_. [[pdf]](https://arxiv.org/pdf/1810.03642.pdf) \n\n* __Meta-Learning for Low-resource Natural Language Generation in Task-oriented Dialogue Systems__, (2019), _Fei Mi, Minlie Huang, Jiyong Zhang, Boi Faltings_. [[pdf]](https://arxiv.org/pdf/1905.05644.pdf)\n\n* __MIND: Model Independent Neural Decoder__, (2019), _Yihan Jiang, Hyeji Kim, Himanshu Asnani, Sreeram Kannan_. [[pdf]](https://arxiv.org/pdf/1903.02268.pdf)\n\n* __Toward Multimodal Model-Agnostic Meta-Learning__, (2018), _Risto Vuorio, Shao-Hua Sun, Hexiang Hu, Joseph J. Lim_. [[pdf]](https://arxiv.org/pdf/1812.07172.pdf) \n\n* __Alpha MAML: Adaptive Model-Agnostic Meta-Learning__, (2019), _Harkirat Singh Behl, Atılım Güneş Baydin, Philip H. S. Torr._  [[pdf]](https://arxiv.org/pdf/1905.07435.pdf)\n\n* __Online Meta-Learning__, (2019), Chelsea Finn, _Aravind Rajeswaran, Sham Kakade, Sergey Levine_. [[pdf]](https://arxiv.org/pdf/1902.08438.pdf)\n\n\n\n### [Meta Reinforcement Learning]()\n\n* __Generalizing Skills with Semi-Supervised Reinforcement Learning__, (2017), _Chelsea Finn, Tianhe Yu, Justin Fu, Pieter Abbeel, Sergey Levine_. [[pdf]](https://arxiv.org/pdf/1612.00429.pdf) [[code]](https://github.com/cbfinn/gps/tree/ssrl)\n\n* __Guided Meta-Policy Search__, (2019), _Russell Mendonca, Abhishek Gupta, Rosen Kralev, Pieter Abbeel, Sergey Levine, Chelsea Finn_. [[pdf]](https://arxiv.org/pdf/1904.00956.pdf) [[code]](https://github.com/RussellM2020/GMPS)\n\n* __End-to-End Robotic Reinforcement Learning without Reward Engineering__, (2019), _Avi Singh, Larry Yang, Kristian Hartikainen, Chelsea Finn, Sergey Levine_. [[pdf]](https://arxiv.org/abs/1904.07854) [[code]](https://github.com/avisingh599/reward-learning-rl)\n\n* __Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables__, (2019), _Kate Rakelly, Aurick Zhou, Deirdre Quillen, Chelsea Finn, Sergey Levine_. [[pdf]](https://arxiv.org/pdf/1903.08254) [[code]](https://github.com/katerakelly/oyster)\n\n* __Meta-Gradient Reinforcement Learning__, (2018), _Zhongwen Xu, Hado van Hasselt,David Silver_. [[pdf]](http://papers.nips.cc/paper/7507-meta-gradient-reinforcement-learning.pdf)\n\n* __Task-Agnostic Dynamics Priors for Deep Reinforcement Learning__, (2019), _Yilun Du, Karthik Narasimhan_. [[pdf]](https://arxiv.org/pdf/1905.04819.pdf)\n\n* __Meta Reinforcement Learning with Task Embedding and Shared Policy__,(2019), _Lin Lan, Zhenguo Li, Xiaohong Guan, Pinghui Wang_. [[pdf]](https://arxiv.org/pdf/1905.06527.pdf) \n\n* __NoRML: No-Reward Meta Learning__, (2019), _Yuxiang Yang, Ken Caluwaerts, Atil Iscen, Jie Tan, Chelsea Finn_. [[pdf]](https://arxiv.org/pdf/1903.01063.pdf)\n\n* __Actor-Critic Algorithms for Constrained Multi-agent Reinforcement Learning__, (2019), _Raghuram Bharadwaj Diddigi, Sai Koti Reddy Danda, Prabuchandran K. J., Shalabh Bhatnagar_. [[pdf]](https://arxiv.org/pdf/1905.02907.pdf)\n\n* __Adaptive Guidance and Integrated Navigation with Reinforcement Meta-Learning__, (2019), _Brian Gaudet, Richard Linares, Roberto Furfaro_. [[pdf]](https://arxiv.org/pdf/1904.09865.pdf)\n\n\n* __Watch, Try, Learn: Meta-Learning from Demonstrations and Reward__, (2019), _Allan Zhou, Eric Jang, Daniel Kappler, Alex Herzog, Mohi Khansari, Paul Wohlhart, Yunfei Bai, Mrinal Kalakrishnan, Sergey Levine, Chelsea Finn_. [[pdf]](https://arxiv.org/pdf/1906.03352.pdf)\n\n* __Options as responses: Grounding behavioural hierarchies in multi-agent RL__, (2019), _Alexander Sasha Vezhnevets, Yuhuai Wu, Remi Leblond, Joel Z. Leibo_. [[pdf]](https://arxiv.org/pdf/1906.01470.pdf)\n\n* __Learning latent state representation for speeding up exploration__, (2019), _Giulia Vezzani, Abhishek Gupta, Lorenzo Natale, Pieter Abbeel_. [[pdf]](https://arxiv.org/pdf/1905.12621.pdf)\n\n* __Beyond Exponentially Discounted Sum: Automatic Learning of Return Function__, (2019), _Yufei Wang, Qiwei Ye, Tie-Yan Liu_. [[pdf]](https://arxiv.org/pdf/1905.11591.pdf)\n\n* __Learning Efficient and Effective Exploration Policies with Counterfactual Meta Policy__, (2019),  _Ruihan Yang, Qiwei Ye, Tie-Yan Liu_. [[pdf]](https://arxiv.org/pdf/1905.11583.pdf)\n\n* __Dealing with Non-Stationarity in Multi-Agent Deep Reinforcement Learning__, (2019), _Georgios Papoudakis, Filippos Christianos, Arrasy Rahman, Stefano V. Albrecht_. [[pdf]](https://arxiv.org/pdf/1906.04737.pdf)\n\n* __Learning to Discretize: Solving 1D Scalar Conservation Laws via Deep Reinforcement Learning__, (2019), _Yufei Wang, Ziju Shen, Zichao Long, Bin Dong_. [[pdf]](https://arxiv.org/pdf/1905.11079.pdf)\n\n\n## [Books]()\n\n* __Hands-On Meta Learning with Python: Meta learning using one-shot learning, MAML, Reptile, and Meta-SGD with TensorFlow__, (2019), _Sudharsan Ravichandiran_. [[pdf]](https://www.amazon.com/Hands-Meta-Learning-Python-TensorFlow-ebook/dp/B07KJJHYKF/ref=tmm_kin_swatch_0?_encoding=UTF8\u0026qid=\u0026sr=) [[code]](https://github.com/sudharsan13296/Hands-On-Meta-Learning-With-Python)\n\n\n## Libraries\n\n* [Higher by Facebook research](https://github.com/facebookresearch/higher)\n* [TorchMeta](https://github.com/tristandeleu/pytorch-meta)\n* [Learn2learn]( https://github.com/learnables/learn2learn)\n\n\n## Blogs\n\n* [Berkeley Artificial Intelligence Research blog](https://bair.berkeley.edu/blog/2017/07/18/learning-to-learn/)\n\n* [Meta-Learning: Learning to Learn Fast](https://lilianweng.github.io/lil-log/2018/11/30/meta-learning.html)\n\n* [Meta-Reinforcement Learning](https://blog.floydhub.com/meta-rl/)\n\n* [How to train your MAML: A step by step approach](https://www.bayeswatch.com/2018/11/30/HTYM/)\n\n* [An Introduction to Meta-Learning](https://medium.com/walmartlabs/an-introduction-to-meta-learning-ced7072b80e7)\n\n* [From zero to research — An introduction to Meta-learning](https://medium.com/huggingface/from-zero-to-research-an-introduction-to-meta-learning-8e16e677f78a)\n\n* [What’s New in Deep Learning Research: Understanding Meta-Learning](https://towardsdatascience.com/whats-new-in-deep-learning-research-understanding-meta-learning-91fef1295660) \n\n* [Meta Reinforcement Learning Blog by Lilian Weng](https://lilianweng.github.io/lil-log/2019/06/23/meta-reinforcement-learning.html)\n\n## Lecture Videos \n\n* [Stanford CS330: Multi-Task and Meta-Learning, 2019 by Chelsea Finn](https://youtu.be/0rZtSwNOTQo)\n\n* [Meta Learning lecture by Soheil Feizi](https://www.youtube.com/watch?v=CRHKgOYXVe8)\n\n* [Chelsea Finn: Building Unsupervised Versatile Agents with Meta-Learning](https://www.youtube.com/watch?v=i05Fk4ebMY0)\n\n* [Sam Ritter: Meta-Learning to Make Smart Inferences from Small Data](https://www.youtube.com/watch?v=NpSpHlHpz6k)\n\n* [Model Agnostic Meta Learning by Siavash Khodadadeh](https://www.youtube.com/watch?v=wT45v8sIMDM)\n\n* [Meta Learning by Siraj Raval](https://www.youtube.com/watch?v=2z0ofe2lpz4)\n\n* [Meta Learning by Hugo Larochelle](https://www.youtube.com/watch?v=lz0ekIVfoFs) \n\n* [Meta Learning and One-Shot Learning](https://www.youtube.com/watch?v=KUWywwvQv8E)\n\n\n\n\n## Datasets\n\nMost popularly used datasets:\n\n* [Omniglot](https://github.com/brendenlake/omniglot) \n* [mini-ImageNet](https://github.com/y2l/mini-imagenet-tools) \n* [ILSVRC](http://image-net.org/challenges/LSVRC/)\n* [FGVC aircraft](http://www.robots.ox.ac.uk/~vgg/data/fgvc-aircraft/)\n* [Caltech-UCSD Birds-200-2011](http://www.vision.caltech.edu/visipedia/CUB-200-2011.html)\n\nCheck several other datasets by Google [here.](https://github.com/google-research/meta-dataset)\n\n\n## Workshops\n\n* [MetaLearn 2017](http://metalearning.ml/2017/)\n* [MetaLearn 2018](http://metalearning.ml/2018/)\n* [MetaLearn 2019](http://metalearning.ml/2019/)\n* [MetaLearn 2020](https://meta-learn.github.io/2020/)\n\n\n## Researchers\n\n* [Chelsea Finn](http://people.eecs.berkeley.edu/~cbfinn/), _UC Berkeley_\n* [Pieter Abbeel](https://people.eecs.berkeley.edu/~pabbeel/), _UC Berkeley_\n* [Erin Grant](https://people.eecs.berkeley.edu/~eringrant/),  _UC Berkeley_\n* [Raia Hadsell](http://raiahadsell.com/index.html), _DeepMind_\n* [Misha Denil](http://mdenil.com/), _DeepMind_\n* [Adam Santoro](https://scholar.google.com/citations?hl=en\u0026user=evIkDWoAAAAJ\u0026view_op=list_works\u0026sortby=pubdate), _DeepMind_\n* [Sachin Ravi](http://www.cs.princeton.edu/~sachinr/), _Princeton University_\n* [David Abel](https://david-abel.github.io/), _Brown University_\n* [Brenden Lake](https://cims.nyu.edu/~brenden/), _Facebook AI Research_\n\n\n## Contributions\n\nContributions are most welcome, if you have any suggestions and improvements, please create an issue or raise a pull request. \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsudharsan13296%2FAwesome-Meta-Learning","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsudharsan13296%2FAwesome-Meta-Learning","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsudharsan13296%2FAwesome-Meta-Learning/lists"}