Topic: meta-learning Goto Github
Some thing interesting about meta-learning
Some thing interesting about meta-learning
meta-learning,Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
User: jindongwang
Home Page: http://transferlearning.xyz/
meta-learning,Automated Machine Learning with scikit-learn
Organization: automl
Home Page: https://automl.github.io/auto-sklearn
meta-learning,A PyTorch Library for Meta-learning Research
Organization: learnables
Home Page: http://learn2learn.net
meta-learning,Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning
User: floodsung
meta-learning,Implementation of papers in 100 lines of code.
User: maximevandegar
meta-learning,A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch
User: tristandeleu
Home Page: https://tristandeleu.github.io/pytorch-meta/
meta-learning,FSL-Mate: A collection of resources for few-shot learning (FSL).
User: tata1661
meta-learning,Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.
Organization: sicara
meta-learning,Repository for few-shot learning machine learning projects
User: oscarknagg
meta-learning,PyTorch code for CVPR 2018 paper: Learning to Compare: Relation Network for Few-Shot Learning (Few-Shot Learning part)
User: floodsung
meta-learning,[TPAMI 2023] LibFewShot: A Comprehensive Library for Few-shot Learning.
Organization: rl-vig
meta-learning,Collection for Few-shot Learning
User: duan-jm
meta-learning,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.
User: guan-yuan
meta-learning,A dataset of datasets for learning to learn from few examples
Organization: google-research
meta-learning,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..
User: omerbsezer
meta-learning,TensorFlow and PyTorch implementation of "Meta-Transfer Learning for Few-Shot Learning" (CVPR2019)
User: yaoyao-liu
Home Page: https://lyy.mpi-inf.mpg.de/mtl/
meta-learning,All materials you need for Federated Learning: blogs, videos, papers, and softwares, etc.
User: weimingwill
Home Page: https://github.com/EasyFL-AI/EasyFL
meta-learning,Manipulating Python Programs
Organization: google
meta-learning,Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. ACM Computing Surveys, 2026.
User: ennengyang
Home Page: https://arxiv.org/pdf/2408.07666
meta-learning,Awesome Multitask Learning Resources
User: mbs0221
meta-learning,Accompanying code for "Discovering State-of-the-art Reinforcement Algorithms" Nature publication
Organization: google-deepmind
Home Page: https://google-deepmind.github.io/disco_rl
meta-learning,TorchOpt is an efficient library for differentiable optimization built upon PyTorch.
Organization: metaopt
Home Page: https://torchopt.readthedocs.io
meta-learning,Meta-Learning with Differentiable Convex Optimization (CVPR 2019 Oral)
User: kjunelee
meta-learning,[CVPR'17] Training a Correlation Filter end-to-end allows lightweight networks of 2 layers (600 kB) to high performance at fast speed..
User: bertinetto
meta-learning,Knowledge-Aware machine LEarning (KALE): accessible machine learning from multiple sources for interdisciplinary research, part of the 🔥PyTorch ecosystem. ⭐ Star to support our work!
Organization: pykale
Home Page: https://pykale.github.io/
meta-learning,Tools for generating mini-ImageNet dataset and processing batches
User: yaoyao-liu
Home Page: https://mtl.yyliu.net/datasets/
meta-learning,Great resources for making Reinforcement Learning work in Real Life situations. Papers,projects and more.
User: ugurkanates
meta-learning,The code repository for "Few-Shot Learning via Embedding Adaptation with Set-to-Set Functions"
Organization: sha-lab
meta-learning,[T-PAMI 2022] Meta-DETR for Few-Shot Object Detection: Official PyTorch Implementation
User: zhanggongjie
meta-learning,PyTorch code for Learning Deep Time-index Models for Time Series Forecasting (ICML 2023)
Organization: salesforce
meta-learning,A classified list of meta learning papers based on realm.
User: jensen888
meta-learning,A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning. TPAMI, 2024.
User: ennengyang
Home Page: https://arxiv.org/abs/2307.09218
meta-learning,Cross-Domain Few-Shot Classification via Learned Feature-Wise Transformation (ICLR 2020 spotlight)
User: hytseng0509
meta-learning,Betty: an automatic differentiation library for generalized meta-learning and multilevel optimization
Organization: leopard-ai
Home Page: https://leopard-ai.github.io/betty/
meta-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
User: gitabcworld
meta-learning,OpenML's Python API for a World of Data and More 💫
Organization: openml
Home Page: http://openml.github.io/openml-python/latest/
meta-learning,PyTorch Implementations For A Series Of Deep Learning-Based Recommendation Models
User: khanhnamle1994
meta-learning,Collection of Reinforcement Learning / Meta Reinforcement Learning Environments.
Organization: paddlepaddle
meta-learning,Open-L2O: A Comprehensive and Reproducible Benchmark for Learning to Optimize Algorithms
Organization: vita-group
meta-learning,Code for "One-Shot Visual Imitation Learning via Meta-Learning"
User: tianheyu927
Home Page: https://sites.google.com/view/one-shot-imitation
meta-learning,NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).
User: xjtushujun
meta-learning,META‑AGENTIC α‑AGI 👁️✨ — Mission 🎯 End‑to‑end: Identify 🔍 → Out‑Learn 📚 → Out‑Think 🧠 → Out‑Design 🎨 → Out‑Strategise ♟️ → Out‑Execute ⚡
User: montrealai
Home Page: https://montreal.ai/
meta-learning,Meta-Transfer Learning for Zero-Shot Super-Resolution (CVPR, 2020)
User: jwsoh
meta-learning,A resource list for causality in statistics, data science and physics
User: msuzen
meta-learning,Implementations of many meta-learning algorithms to solve the few-shot learning problem in Pytorch
User: cnguyen10
meta-learning,Code for the paper "Evolved Policy Gradients"
Organization: openai
Home Page: https://arxiv.org/abs/1802.04821
meta-learning,Official implementation of Meta-StyleSpeech and StyleSpeech
User: kevinmin95
meta-learning,Implementation of Proximal Meta-Policy Search (ProMP) as well as related Meta-RL algorithm. Includes a useful experiment framework for Meta-RL.
User: jonasrothfuss
Home Page: https://sites.google.com/view/pro-mp
meta-learning,A PyTorch implementation of Model Agnostic Meta-Learning (MAML) that faithfully reproduces the results from the original paper.
User: shirleyzhu233
meta-learning,A list of recent papers about Meta / few-shot learning methods applied in NLP areas.
User: ha-lins
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A server is a program made to process requests and deliver data to clients.
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Some thing interesting about visualization, use data art
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Open source projects and samples from Microsoft.
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