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Continual Learning

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평가표: 33
보존된 평가 기록: 133

Continual Learning (also known as Incremental Learning, Life-long Learning) is a concept to learn a model for a large number of tasks sequentially without forgetting knowledge obtained from the preceding tasks, where the data in the old tasks are not available anymore during training new ones.
If not mentioned, the benchmarks here are Task-CL, where task-id is provided on validation.

Source:
Continual Learning by Asymmetric Loss Approximation with Single-Side Overestimation
Three scenarios for continual learning
Lifelong Machine Learning
Continual lifelong learning with neural networks: A review

코드

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

https://github.com/zwx8981/BIQA_CL

공식 코드

Continual Learning for Blind Image Quality Assessment

https://github.com/zwx8981/tsn-iqa

공식 코드

Task-Specific Normalization for Continual Learning of Blind Image Quality Models

https://github.com/zyl24/fcgl_power

공식 코드

Federated Continual Graph Learning

https://github.com/zylMozart/TaskDrop

공식 코드

TaskDrop: A Competitive Baseline for Continual Learning of Sentiment Classification

https://github.com/zysong0113/savc

공식 코드

Learning with Fantasy: Semantic-Aware Virtual Contrastive Constraint for Few-Shot Class-Incremental Learning

https://github.com/zyuh/bdr-main

공식 코드

Balanced Destruction-Reconstruction Dynamics for Memory-replay Class Incremental Learning

https://github.com/zzz47zzz/CFNER

공식 코드

Distilling Causal Effect from Miscellaneous Other-Class for Continual Named Entity Recognition

https://github.com/zzz47zzz/codebase-for-incremental-learning-with-llm

공식 코드

Learn or Recall? Revisiting Incremental Learning with Pre-trained Language Models

https://github.com/zzz47zzz/pretrained-lm-for-incremental-learning

공식 코드

Learn or Recall? Revisiting Incremental Learning with Pre-trained Language Models

https://github.com/zzz47zzz/spurious-forgetting

공식 코드

Spurious Forgetting in Continual Learning of Language Models

https://gitlab.com/prakhark2/relevance-mapping-networks

공식 코드

Understanding Catastrophic Forgetting and Remembering in Continual Learning with Optimal Relevance Mapping

https://gitlab.com/viper-purdue/continual-compression

공식 코드

Towards Backward-Compatible Continual Learning of Image Compression

https://gitlab.com/viper-purdue/delta

공식 코드

DELTA: Decoupling Long-Tailed Online Continual Learning

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

공식 코드

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

https://gitlab.mpi-klsb.mpg.de/yaoyaoliu/rmm

공식 코드

RMM: Reinforced Memory Management for Class-Incremental Learning

https://gitlab.mpi-klsb.mpg.de/yaoyaoliu/rmm/

공식 코드

RMM: Reinforced Memory Management for Class-Incremental Learning

https://github.com/2023-MindSpore-1/ms-code-70

Learning Adaptive Embedding Considering Incremental Class

https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/blenderbot

BlenderBot 3: a deployed conversational agent that continually learns to responsibly engage

https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/blenderbot_small

BlenderBot 3: a deployed conversational agent that continually learns to responsibly engage

https://github.com/A-Roucher/variational_continual_learning

Variational Continual Learning

https://github.com/AndreevP/FRCL

Functional Regularisation for Continual Learning with Gaussian Processes

https://github.com/AntreasAntoniou/FewShotContinualLearningDataProvider

Defining Benchmarks for Continual Few-Shot Learning

https://github.com/BITCS-Information-Retrieval-2020/search-rattailcollagen1

Unifying Regularisation Methods for Continual Learning

https://github.com/Chandan-IITI/Tf-GCZSL

Online Lifelong Generalized Zero-Shot Learning

https://github.com/ChristosKap/policy_consolidation

Policy Consolidation for Continual Reinforcement Learning

https://github.com/DRSAD/iCaRL

iCaRL: Incremental Classifier and Representation Learning

https://github.com/DavidBurt2/Rates-of-Convergence-SGPR

Rates of Convergence for Sparse Variational Gaussian Process Regression

https://github.com/DennisReddyhoff/ContinualGP

Continual Multi-task Gaussian Processes

https://github.com/DuoJiang/Meta-Continual-Learning-NLP

Meta-Learning Representations for Continual Learning

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

Three scenarios for continual learning

https://github.com/GuangpingYuan/PNN_Pong_A3C

Progressive Neural Networks

https://github.com/GuoQuanhao/SupContrast-Paddle

Supervised Contrastive Learning

https://github.com/Guy-Shapira/DeepInversion

Dreaming to Distill: Data-free Knowledge Transfer via DeepInversion

https://github.com/Haoran-S/SPAWC2017

Learning to Continuously Optimize Wireless Resource In Episodically Dynamic Environment

https://github.com/Haoran-S/TSP-DNN

Learning to Continuously Optimize Wireless Resource In Episodically Dynamic Environment

https://github.com/IntelLabs/bayesian-torch

Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning

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