Trending repositories for topic meta-learning
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
LibFewShot: A Comprehensive Library for Few-shot Learning. TPAMI 2023.
Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.
Implementation of the paper "Adversarial Attacks on Graph Neural Networks via Meta Learning".
[T-PAMI 2022] Meta-DETR for Few-Shot Object Detection: Official PyTorch Implementation
All materials you need for Federated Learning: blogs, videos, papers, and softwares, etc.
Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
Implementation of the paper "Adversarial Attacks on Graph Neural Networks via Meta Learning".
[T-PAMI 2022] Meta-DETR for Few-Shot Object Detection: Official PyTorch Implementation
LibFewShot: A Comprehensive Library for Few-shot Learning. TPAMI 2023.
Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.
A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch
All materials you need for Federated Learning: blogs, videos, papers, and softwares, etc.
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch
A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning. TPAMI, 2024.
Implementation of papers in 100 lines of code.
Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.
[Paper][ACM MM 2023] MEAformer: Multi-modal Entity Alignment Transformer for Meta Modality Hybrid
🎓 Automatically Update Some Fields Papers Daily using Github Actions (Update Every 12th hours)
An index of algorithms for few-shot learning/meta-learning on graphs
Implementation of the paper "Adversarial Attacks on Graph Neural Networks via Meta Learning".
[T-PAMI 2022] Meta-DETR for Few-Shot Object Detection: Official PyTorch Implementation
All materials you need for Federated Learning: blogs, videos, papers, and softwares, etc.
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.) Hype...
Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
[Paper][ACM MM 2023] MEAformer: Multi-modal Entity Alignment Transformer for Meta Modality Hybrid
A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning. TPAMI, 2024.
🎓 Automatically Update Some Fields Papers Daily using Github Actions (Update Every 12th hours)
An index of algorithms for few-shot learning/meta-learning on graphs
Implementation of the paper "Adversarial Attacks on Graph Neural Networks via Meta Learning".
Implementation of papers in 100 lines of code.
[T-PAMI 2022] Meta-DETR for Few-Shot Object Detection: Official PyTorch Implementation
Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.
A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch
All materials you need for Federated Learning: blogs, videos, papers, and softwares, etc.
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
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.) Hype...
Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
Implementation of papers in 100 lines of code.
Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.
A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning. TPAMI, 2024.
All materials you need for Federated Learning: blogs, videos, papers, and softwares, etc.
A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch
LibFewShot: A Comprehensive Library for Few-shot Learning. TPAMI 2023.
IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning
An index of algorithms for few-shot learning/meta-learning on graphs
A PyTorch implementation of Model Agnostic Meta-Learning (MAML) that faithfully reproduces the results from the original paper.
TorchOpt is an efficient library for differentiable optimization built upon PyTorch.
🎓 Automatically Update Some Fields Papers Daily using Github Actions (Update Every 12th hours)
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.) Hype...
IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
Official implementation for ActFound: A bioactivity foundation model using pairwise meta-learning
A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning. TPAMI, 2024.
Official code repository for "Meta Learning to Bridge Vision and Language Models for Multimodal Few-Shot Learning" (published at ICLR 2023).
Codes for "Property-Aware Relation Networks for Few-shot Molecular Property Prediction (NeurIPS 2021)".
An index of algorithms for few-shot learning/meta-learning on graphs
Implementation of papers in 100 lines of code.
Abstract thinking patterns and problem decomposition / solving strategies
Meta QLearning experiments to optimize robot walking patterns
[Paper][ACM MM 2023] MEAformer: Multi-modal Entity Alignment Transformer for Meta Modality Hybrid
🎓 Automatically Update Some Fields Papers Daily using Github Actions (Update Every 12th hours)
Code for "Task-Agnostic Continual RL: In Praise of a Simple Baseline"
Code snippets of Meta Reinforcement Learning algorithms
A PyTorch implementation of Model Agnostic Meta-Learning (MAML) that faithfully reproduces the results from the original paper.
A PyTorch implementation of a few shot, and meta-learning algorithms for image classification.
Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.
The official API of DoubleAdapt (KDD'23), an incremental learning framework for online stock trend forecasting, WITHOUT dependencies on the qlib package.
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
Official Repository for "Tamper-Resistant Safeguards for Open-Weight LLMs"
Official PyTorch implementation of "DiffusionNAG: Predictor-guided Neural Architecture Generation with Diffusion Models" (ICLR 2024)
IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning
Abstract thinking patterns and problem decomposition / solving strategies
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.
Implementation of papers in 100 lines of code.
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
LibFewShot: A Comprehensive Library for Few-shot Learning. TPAMI 2023.
A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning. TPAMI, 2024.
A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch
TorchOpt is an efficient library for differentiable optimization built upon PyTorch.
TensorFlow and PyTorch implementation of "Meta-Transfer Learning for Few-Shot Learning" (CVPR2019)
🎓 Automatically Update Some Fields Papers Daily using Github Actions (Update Every 12th hours)
All materials you need for Federated Learning: blogs, videos, papers, and softwares, etc.
An index of algorithms for few-shot learning/meta-learning on graphs
Datasets collection and preprocessings framework for NLP extreme multitask learning
The official API of DoubleAdapt (KDD'23), an incremental learning framework for online stock trend forecasting, WITHOUT dependencies on the qlib package.
Official implementation for ActFound: A bioactivity foundation model using pairwise meta-learning
A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning. TPAMI, 2024.
NAACL '24 (Best Demo Paper RunnerUp) / MlSys @ NeurIPS '23 - RedCoast: A Lightweight Tool to Automate Distributed Training and Inference
🎉🎨 This repository contains a reading list of papers with code on **Meta-Learning** and ***Meta-Reinforcement-Learning*
[Paper][ACM MM 2023] MEAformer: Multi-modal Entity Alignment Transformer for Meta Modality Hybrid
The official API of DoubleAdapt (KDD'23), an incremental learning framework for online stock trend forecasting, WITHOUT dependencies on the qlib package.
Meta QLearning experiments to optimize robot walking patterns
Source code for MetaKG: Meta-learning on Knowledge Graph for Cold-start Recommendation. TKDE 2022.
🎓 Automatically Update Some Fields Papers Daily using Github Actions (Update Every 12th hours)
[ICML 2023] "Towards Omni-generalizable Neural Methods for Vehicle Routing Problems"
Implementation of papers in 100 lines of code.
This project is the official implementation of 'Meta-Learning based Degradation Representation for Blind Super-Resolution', TIP2023
An index of algorithms for few-shot learning/meta-learning on graphs
This repository is for the Few-shot Learning for the fault diagnosis of large industrial equipment.
Datasets collection and preprocessings framework for NLP extreme multitask learning
Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.
Official code repository for "Meta Learning to Bridge Vision and Language Models for Multimodal Few-Shot Learning" (published at ICLR 2023).
Code for ICCV 2021 paper: 'Query Adaptive Few-Shot Object Detection with Heterogeneous Graph Convolutional Networks'