Related work

The foundational work on continual learning, 1959 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

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2020 Neurocomputing Clear all

2020
SpaceNet: Make Free Space For Continual LearningGhada Sokar, Decebal Constantin Mocanu, Mykola PechenizkiyNeurocomputing · Eindhoven University of Technology · University of Twente
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2020
Motivational engine and long-term memory coupling within a cognitive architecture for lifelong open-ended learningJ. A. Becerra, Alejandro Romero, Francisco Bellas, Richard J. DuroNeurocomputing · Universidade da Coruña
2020
A sparse code increases the speed and efficiency of neuro-dynamic programming for optimal control tasks with correlated inputsPeter LoxleyNeurocomputing · University of New England
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2020
BNGBS: An efficient network boosting system with triple incremental learning capabilities for more nodes, samples, and classesLiangjun Feng, Chunhui Zhao, C. L. Philip Chen … Chuan FuNeurocomputing · State Key Laboratory of Industrial Control Technology · University of Macau · +1
2020
An effective maximum entropy exploration approach for deceptive game in reinforcement learningChunmao Li, Xuanguang Wei, Yinliang Zhao, Xupeng GengNeurocomputing · Xi'an Jiaotong University
2020
OSCD: A one-shot conditional object detection frameworkKun Fu, Tengfei Zhang, Yue Zhang, Xian SunNeurocomputing · Chinese Academy of Sciences · Institute of Electronics · +2
2020
Relevance feedback based online learning model for resource bottleneck prediction in cloud serversShaifu Gupta, A. D. DileepNeurocomputing · Indian Institute of Technology Mandi
2020
Parallel Multi-Environment Shaping Algorithm for Complex Multi-step TaskCong Ma, Zhizhong Li, Dahua Lin, Jiangshe ZhangNeurocomputing · Xi'an Jiaotong University · Hong Kong Science and Technology Parks Corporation · +1
2020
Prevention of catastrophic interference and imposing active forgetting with generative methodsSergey Sukhov, Mikhail Leontev, Alexander Miheev, Kirill SviatovNeurocomputing · Kotelnikov Institute of Radioengineering and Electronics of the Russian Academy of Sciences · Ulyanovsk State University · +1
2020
Prediction of blood glucose concentration for type 1 diabetes based on echo state networks embedded with incremental learningNing Li, Jianyong Tuo, Youqing Wang, Menghui WangNeurocomputing · Beijing University of Chemical Technology · Shandong University of Science and Technology

About this index

We keep this list because we read the field and wanted one place to see it. It covers work on continual learning itself, in the core areas of machine learning, and leaves out papers that apply it inside another field, such as medical imaging or fault diagnosis. It is seeded from the community lists kept by ContinualAI and by Xialei Liu, then filled out from OpenAlex, and every week a script looks for new papers on OpenAlex and arXiv. A model reads each candidate and decides whether it belongs; a person reviews the additions before they go live. Authors and affiliations come from OpenAlex, so a recent preprint can lack its institutions for a week or two.

Missing something, or filed under the wrong venue? Write to hello@unify.ai with the arXiv id or DOI.