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Lifelong learning

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/rahafaljundi/Selfless-Sequential-Learning

공식 코드

Selfless Sequential Learning

https://github.com/restrada1/continual-learning

공식 코드

Self-Net: Lifelong Learning via Continual Self-Modeling

https://github.com/ruidaniel/rbaca

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Continual Deep Active Learning for Medical Imaging: Replay-Base Architecture for Context Adaptation

https://github.com/s4nyam/cqural

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CQural: A Novel CNN based Hybrid Architecture for Quantum Continual Machine Learning

https://github.com/sahanbull/TrueLearn

공식 코드

TrueLearn: A Family of Bayesian Algorithms to Match Lifelong Learners to Open Educational Resources

https://github.com/sanketvmehta/lifelong-learning-pretraining-and-sam

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An Empirical Investigation of the Role of Pre-training in Lifelong Learning

https://github.com/siat-nlp/IPRLS

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Iterative Network Pruning with Uncertainty Regularization for Lifelong Sentiment Classification

https://github.com/sisl/MPHRL

공식 코드

Model Primitive Hierarchical Lifelong Reinforcement Learning

https://github.com/soltoggio/ct-graph

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Lifelong Reinforcement Learning with Modulating Masks

https://github.com/spearsheep/APT-Architectural-Planning-LLM-Agent

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APT: Architectural Planning and Text-to-Blueprint Construction Using Large Language Models for Open-World Agents

https://github.com/tailintalent/AI_physicist

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Toward an AI Physicist for Unsupervised Learning

https://github.com/thunlp/elle

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ELLE: Efficient Lifelong Pre-training for Emerging Data

https://github.com/uber-common/differentiable-plasticity

공식 코드

Differentiable plasticity: training plastic neural networks with backpropagation

https://github.com/uvm-neurobotics-lab/ANML

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Learning to Continually Learn

https://github.com/vc-yang/multiscale_learning_model

공식 코드

Mathematical model bridges disparate timescales of lifelong learning

https://github.com/vgaraujov/esp-cl

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Entropy-based Stability-Plasticity for Lifelong Learning

https://github.com/villawang/CatNet

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CatNet: Class Incremental 3D ConvNets for Lifelong Egocentric Gesture Recognition

https://github.com/vt-nlp/incremental_prompting

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Incremental Prompting: Episodic Memory Prompt for Lifelong Event Detection

https://github.com/wang-chen/LGL

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Lifelong Graph Learning

https://github.com/wang-chen/airloop

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AirLoop: Lifelong Loop Closure Detection

https://github.com/wang-chen/lgl-action-recognition

공식 코드

Lifelong Graph Learning

https://github.com/wcyno23/shlpt

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Mitigate Negative Transfer with Similarity Heuristic Lifelong Prompt Tuning

https://github.com/wenjinw/par

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Task Difficulty Aware Parameter Allocation & Regularization for Lifelong Learning

https://github.com/xialeiliu/RotateNetworks

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Rotate your Networks: Better Weight Consolidation and Less Catastrophic Forgetting

https://github.com/xiaojiegu/ultraedit

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UltraEdit: Training-, Subject-, and Memory-Free Lifelong Editing in Large Language Models

https://github.com/xiaozeroone/conditional_finetune

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Conditional Language Learning with Context

https://github.com/zh460045050/LNSNet

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Learning the Superpixel in a Non-iterative and Lifelong Manner

https://gitlab.com/viper-purdue/ocil-real-world-food-image-classification

공식 코드

Online Class-Incremental Learning For Real-World Food Image Classification

https://github.com/ContinualAI/avalanche

Expert Gate: Lifelong Learning with a Network of Experts

https://github.com/DMIU-ShELL/MOSAIC

Lifelong Reinforcement Learning with Modulating Masks

https://github.com/GMC-DRL/ConfigX

ConfigX: Modular Configuration for Evolutionary Algorithms via Multitask Reinforcement Learning

https://github.com/GMvandeVen/complex-synapses

Three scenarios for continual learning

https://github.com/MindSpore-scientific-2/code-12/tree/main/LGL-INR-master

Lifelong Graph Learning

https://github.com/ModelDBRepository/261864

Rapid online learning and robust recall in a neuromorphic olfactory circuit

https://github.com/Ramos-Ramos/FlyModel

Algorithmic insights on continual learning from fruit flies

https://github.com/ThomasMiconi/LearningToLearnBOHP

Learning to learn with backpropagation of Hebbian plasticity

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