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https://github.com/floodsung/Lifelong-Learning-Paper-List
Lifelong/Continual Learning Paper List
https://github.com/floodsung/Lifelong-Learning-Paper-List
Last synced: 3 months ago
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Lifelong/Continual Learning Paper List
- Host: GitHub
- URL: https://github.com/floodsung/Lifelong-Learning-Paper-List
- Owner: floodsung
- License: mit
- Created: 2018-11-30T03:22:16.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2018-11-30T04:13:39.000Z (almost 6 years ago)
- Last Synced: 2024-05-13T00:36:53.132Z (6 months ago)
- Size: 2.93 KB
- Stars: 150
- Watchers: 10
- Forks: 20
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-machine-learning-resources - **[List - Learning-Paper-List?style=social) (Table of Contents)
README
# Lifelong Learning / Continual Learning
**[1]** Parisi, German I., et al. **Continual Lifelong Learning with Neural Networks: A Review.** arXiv preprint arXiv:1802.07569 (2018). [link](https://arxiv.org/pdf/1802.07569)
**[2]** Gepperth, Alexander, and Cem Karaoguz. **A bio-inspired incremental learning architecture for applied perceptual problems.** Cognitive Computation 8.5 (2016): 924-934. [link](https://hal.archives-ouvertes.fr/hal-01418123/file/article.pdf)
**[3]** Lüders, Benno, Mikkel Schläger, and Sebastian Risi. **Continual learning through evolvable neural turing machines.** NIPS 2016 Workshop on Continual Learning and Deep Networks (CLDL 2016). 2016. [link](http://sebastianrisi.com/wp-content/uploads/lueders_CLDL_NIPS2016.pdf)
**[4]** Shin, Hanul, et al. **Continual learning with deep generative replay.** Advances in Neural Information Processing Systems. 2017. [link](http://papers.nips.cc/paper/6892-continual-learning-with-deep-generative-replay.pdf)
**[5]** Maltoni, Davide, and Vincenzo Lomonaco. **Continuous Learning in Single-Incremental-Task Scenarios.** arXiv preprint arXiv:1806.08568 (2018). [link](https://arxiv.org/pdf/1806.08568)
**[6]** Lomonaco, Vincenzo, and Davide Maltoni. **Core50: a new dataset and benchmark for continuous object recognition.** arXiv preprint arXiv:1705.03550 (2017). [link](https://arxiv.org/pdf/1705.03550)
**[7]** Kamra, Nitin, Umang Gupta, and Yan Liu. **Deep Generative Dual Memory Network for Continual Learning.** arXiv preprint arXiv:1710.10368 (2017). [link](https://arxiv.org/pdf/1710.10368)
**[8]** Triki, Amal Rannen, et al. **Encoder based lifelong learning.** arXiv preprint arXiv:1704.01920 (2017). [link](https://arxiv.org/pdf/1704.01920)
**[9]** Aljundi, Rahaf, Punarjay Chakravarty, and Tinne Tuytelaars. **Expert Gate: Lifelong Learning with a Network of Experts.** CVPR. 2017. [link](http://openaccess.thecvf.com/content_cvpr_2017/papers/Aljundi_Expert_Gate_Lifelong_CVPR_2017_paper.pdf)
**[10]** Rebuffi, Sylvestre-Alvise, et al. **icarl: Incremental classifier and representation learning.** Proc. CVPR. 2017. [link](http://openaccess.thecvf.com/content_cvpr_2017/papers/Rebuffi_iCaRL_Incremental_Classifier_CVPR_2017_paper.pdf)
**[11]** Castro, Francisco M., et al. **End-to-end incremental learning.** ECCV 2018-European Conference on Computer Vision. 2018. [link](http://openaccess.thecvf.com/content_ECCV_2018/papers/Francisco_M._Castro_End-to-End_Incremental_Learning_ECCV_2018_paper.pdf)
**[12]** Aljundi, Rahaf, et al. **Memory Aware Synapses: Learning what (not) to forget.** arXiv preprint arXiv:1711.09601 (2017). [link](https://arxiv.org/pdf/1711.09601)
**[13]** Kemker, Ronald, and Christopher Kanan. **Fearnet: Brain-inspired model for incremental learning.** arXiv preprint arXiv:1711.10563 (2017). [link](https://arxiv.org/pdf/1711.10563)
**[14]** Li, Zhizhong, and Derek Hoiem. **Learning without forgetting.** IEEE Transactions on Pattern Analysis and Machine Intelligence (2017). [link](https://arxiv.org/pdf/1606.09282)
**[15]** Parisi, German I., et al. **Lifelong Learning of Spatiotemporal Representations with Dual-Memory Recurrent Self-Organization.** arXiv preprint arXiv:1805.10966 (2018). [link](https://arxiv.org/pdf/1805.10966)
**[16]** Vuorio, Risto, et al. **Meta Continual Learning.** arXiv preprint arXiv:1806.06928 (2018). [link](https://arxiv.org/pdf/1806.06928)
**[17]** Kirkpatrick, James, et al. **Overcoming catastrophic forgetting in neural networks.** Proceedings of the national academy of sciences (2017): 201611835. [link](https://pdfs.semanticscholar.org/ee89/738fcc69212b36fb990389d817b5fb7e486b.pdf)
**[18]** Aljundi, Rahaf, Marcus Rohrbach, and Tinne Tuytelaars. **Selfless Sequential Learning.** arXiv preprint arXiv:1806.05421 (2018). [link](https://arxiv.org/pdf/1806.05421)
**[19]** Nguyen, Cuong V., et al. **Variational continual learning.** arXiv preprint arXiv:1710.10628 (2017). [link](https://arxiv.org/pdf/1710.10628)
**[20]** Hou, Saihui, et al. **Lifelong learning via progressive distillation and retrospection.** European Conference on Computer Vision. Springer, Cham, 2018. [link](http://openaccess.thecvf.com/content_ECCV_2018/papers/Saihui_Hou_Progressive_Lifelong_Learning_ECCV_2018_paper.pdf)
**[21]** Zenke, Friedemann, Ben Poole, and Surya Ganguli. **Continual learning through synaptic intelligence.** arXiv preprint arXiv:1703.04200 (2017). [link](https://arxiv.org/pdf/1703.04200)
**[22]** Yoon, Jaehong, et al. "Lifelong Learning with Dynamically Expandable Networks." ICLR(2018). [link](https://openreview.net/pdf?id=Sk7KsfW0-)
**[23]** Ritter, Hippolyt, Aleksandar Botev, and David Barber. "Online Structured Laplace Approximations For Overcoming Catastrophic Forgetting." arXiv preprint arXiv:1805.07810 (2018). [link](https://arxiv.org/pdf/1805.07810)
**[24]** Chaudhry, Arslan, et al. "Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence." arXiv preprint arXiv:1801.10112 (2018). [link](https://arxiv.org/pdf/1801.10112)
**[25]** Lopez-Paz, David. **Gradient episodic memory for continual learning.** Advances in Neural Information Processing Systems. 2017. [link](https://arxiv.org/pdf/1706.08840)
**[26]** Lee, Sang-Woo, et al. **Overcoming catastrophic forgetting by incremental moment matching.** Advances in Neural Information Processing Systems. 2017. [link](https://papers.nips.cc/paper/7051-overcoming-catastrophic-forgetting-by-incremental-moment-matching.pdf)
**[27]** Schwarz, Jonathan, et al. **Progress & Compress: A scalable framework for continual learning.** arXiv preprint arXiv:1805.06370 (2018). [link](https://arxiv.org/pdf/1805.06370.pdf)
**[28]** Rusu, Andrei A., et al. **Progressive neural networks.** arXiv preprint arXiv:1606.04671 (2016). [link](https://arxiv.org/pdf/1606.04671.pdf?)