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
Implementation of papers in 100 lines of code.
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
Implementation of papers in 100 lines of code.
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
Implementation of papers in 100 lines of code.
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.
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
🎓 Automatically Update Some Fields Papers Daily using Github Actions (Update Every 12th hours)
Datasets collection and preprocessings framework for NLP extreme multitask learning
LibFewShot: A Comprehensive Library for Few-shot Learning. TPAMI 2023.
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
🎓 Automatically Update Some Fields Papers Daily using Github Actions (Update Every 12th hours)
Datasets collection and preprocessings framework for NLP extreme multitask learning
Implementation of papers in 100 lines of code.
All materials you need for Federated Learning: blogs, videos, papers, and softwares, etc.
Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.
LibFewShot: A Comprehensive Library for Few-shot Learning. TPAMI 2023.
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
Implementation of papers in 100 lines of code.
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
Great resources for making Reinforcement Learning work in Real Life situations. Papers,projects and more.
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.
Datasets collection and preprocessings framework for NLP extreme multitask learning
A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning. TPAMI, 2024.
LibFewShot: A Comprehensive Library for Few-shot Learning. TPAMI 2023.
All materials you need for Federated Learning: blogs, videos, papers, and softwares, etc.
TorchOpt is an efficient library for differentiable optimization built upon PyTorch.
🎓 Automatically Update Some Fields Papers Daily using Github Actions (Update Every 12th hours)
Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning
Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.
[T-PAMI 2022] Meta-DETR for Few-Shot Object Detection: Official PyTorch Implementation
Implementation of papers in 100 lines of code.
Great resources for making Reinforcement Learning work in Real Life situations. Papers,projects and more.
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
Datasets collection and preprocessings framework for NLP extreme multitask learning
A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning. TPAMI, 2024.
IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning
Official Repository for "Tamper-Resistant Safeguards for Open-Weight LLMs"
🎓 Automatically Update Some Fields Papers Daily using Github Actions (Update Every 12th hours)
Implementation of 'RL^2: Fast Reinforcement Learning via Slow Reinforcement Learning'
Official PyTorch implementation of "DiffusionNAG: Predictor-guided Neural Architecture Generation with Diffusion Models" (ICLR 2024)
Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.
PyTorch Implementation of Personalized federated learning with theoretical guarantees: A model-agnostic meta-learning approach
Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.
A curated list of Artificial Intelligence (AI) Research, tracks the cutting edge trending of AI research, including recommender systems, computer vision, machine learning, etc.
[Paper][ACM MM 2023] MEAformer: Multi-modal Entity Alignment Transformer for Meta Modality Hybrid
All materials you need for Federated Learning: blogs, videos, papers, and softwares, etc.
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
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
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.
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.
Great resources for making Reinforcement Learning work in Real Life situations. Papers,projects and more.
🎓 Automatically Update Some Fields Papers Daily using Github Actions (Update Every 12th hours)
Datasets collection and preprocessings framework for NLP extreme multitask learning
TensorFlow and PyTorch implementation of "Meta-Transfer Learning for Few-Shot Learning" (CVPR2019)
All materials you need for Federated Learning: blogs, videos, papers, and softwares, etc.
Official implementation for ActFound: A bioactivity foundation model using pairwise meta-learning
Implementation of papers in 100 lines of code.
A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning. TPAMI, 2024.
🎉🎨 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
🎓 Automatically Update Some Fields Papers Daily using Github Actions (Update Every 12th hours)
Meta QLearning experiments to optimize robot walking patterns
The official API of DoubleAdapt (KDD'23), an incremental learning framework for online stock trend forecasting, WITHOUT dependencies on the qlib package.
Source code for MetaKG: Meta-learning on Knowledge Graph for Cold-start Recommendation. TKDE 2022.
NAACL '24 (Best Demo Paper RunnerUp) / MlSys @ NeurIPS '23 - RedCoast: A Lightweight Tool to Automate Distributed Training and Inference
[ICML 2023] "Towards Omni-generalizable Neural Methods for Vehicle Routing Problems"
Datasets collection and preprocessings framework for NLP extreme multitask learning
This repository is for the Few-shot Learning for the fault diagnosis of large industrial equipment.
Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.
An index of algorithms for few-shot learning/meta-learning on graphs
Official code repository for "Meta Learning to Bridge Vision and Language Models for Multimodal Few-Shot Learning" (published at ICLR 2023).
This project is the official implementation of 'Meta-Learning based Degradation Representation for Blind Super-Resolution', TIP2023
Code for AAAI 2022 Oral paper: 'Meta Faster R-CNN: Towards Accurate Few-Shot Object Detection with Attentive Feature Alignment'