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Continual learning (CL) learns a sequence of tasks incrementally.
Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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A pac-bayesian bound for lifelong learning
Anastasia Pentina and Christoph Lampert · 2014
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Explaining and harnessing adversarial examples
Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy · 2015
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Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
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Learning Without Forgetting
Zhizhong Li and Derek Hoiem · 2016
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Less-forgetting learning in deep neural networks
Heechul Jung, Jeongwoo Ju, Minju Jung, and Junmo Kim · 2016
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Andrei A Rusu, Neil C Rabinowitz, Guillaume Desjardins, Hubert Soyer, James Kirkpatrick, Koray Kavukcuoglu, Razvan Pascanu, and Raia Hadsell · 2016
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A bio-inspired incremental learning architecture for applied perceptual problems
Alexander Gepperth and Cem Karaoguz · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Sgdr: Stochastic gradient descent with warm restarts
Ilya Loshchilov and Frank Hutter · 2016
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Overcoming catastrophic forgetting in neural networks
James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, et al · 2017
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Incremental robot learning of new objects with fixed update time
Raffaello Camoriano, Giulia Pasquale, Carlo Ciliberto, Lorenzo Natale, Lorenzo Rosasco, and Giorgio Metta · 2017
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Continual learning through synaptic intelligence
Friedemann Zenke, Ben Poole, and Surya Ganguli · 2017
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Gradient Episodic Memory for Continual Learning
David Lopez-Paz and Marc’Aurelio Ranzato · 2017
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iCaRL: Incremental classifier and representation learning
Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, and Christoph H Lampert · 2017
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Deep Generative Dual Memory Network for Continual Learning
Nitin Kamra, Umang Gupta, and Yan Liu · 2017
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Continual learning with deep generative replay
Hanul Shin, Jung Kwon Lee, Jaehong Kim, and Jiwon Kim · 2017
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Continual learning in generative adversarial nets
Ari Seff, Alex Beatson, Daniel Suo, and Han Liu · 2017
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PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning
Arun Mallya and Svetlana Lazebnik · 2017
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Expert gate: Lifelong learning with a network of experts
Rahaf Aljundi, Punarjay Chakravarty, and Tinne Tuytelaars · 2017
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Curiosity-driven exploration by self-supervised prediction
Deepak Pathak, Pulkit Agrawal, Alexei A Efros, and Trevor Darrell · 2017
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Large batch training of convolutional networks
Yang You, Igor Gitman, and Boris Ginsburg · 2017
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Lifelong machine learning
Zhiyuan Chen and Bing Liu · 2018
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Overcoming catastrophic forgetting with hard attention to the task
Joan Serrà, Dídac Surís, Marius Miron, and Alexandros Karatzoglou · 2018
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Enhancing the reliability of out-of-distribution image detection in neural networks
Shiyu Liang, Yixuan Li, and R. Srikant · 2018
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Online structured laplace approximations for overcoming catastrophic forgetting
Hippolyt Ritter, Aleksandar Botev, and David Barber · 2018
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Progress & compress: A scalable framework for continual learning
Jonathan Schwarz, Jelena Luketina, Wojciech M Czarnecki, Agnieszka Grabska-Barwinska, Yee Whye Teh, Razvan Pascanu, and Raia Hadsell · 2018
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Reinforced continual learning
Ju Xu and Zhanxing Zhu · 2018
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End-to-end incremental learning
Francisco M Castro, Manuel J Marín-Jiménez, Nicolás Guil, Cordelia Schmid, and Karteek Alahari · 2018
Cited alongside, same era.
Memory replay gans: Learning to generate new categories without forgetting
Chenshen Wu, Luis Herranz, Xialei Liu, Joost van de Weijer, Bogdan Raducanu, et al · 2018
Cited alongside, same era.
FearNet: Brain-Inspired Model for Incremental Learning
Ronald Kemker and Christopher Kanan · 2018
Cited alongside, same era.
A simple unified framework for detecting out-of-distribution samples and adversarial attacks
Kimin Lee, Kibok Lee, Honglak Lee, and Jinwoo Shin · 2018
Cited alongside, same era.
Three scenarios for continual learning
Gido M van de Ven and Andreas S Tolias · 2019
Cited alongside, same era.
Overcoming catastrophic forgetting for continual learning via model adaptation
Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
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A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
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Anomalous instance detection in deep learning: A survey
Saikiran Bulusu, Bhavya Kailkhura, Bo Li, Pramod K Varshney, and Dawn Song · 2020
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Recent advances in open set recognition: A survey
Chuanxing Geng, Sheng-jun Huang, and Songcan Chen · 2020
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itaml: An incremental task-agnostic meta-learning approach
Jathushan Rajasegaran, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, and Mubarak Shah · 2020
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Wenpeng Hu, Zhou Lin, Bing Liu, Chongyang Tao, Zhengwei Tao, Jinwen Ma, Dongyan Zhao, and Rui Yan · 2019
Cited alongside, same era.
Learning without memorizing
Prithviraj Dhar, Rajat Vikram Singh, Kuan-Chuan Peng, Ziyan Wu, and Rama Chellappa · 2019
Cited alongside, same era.
Overcoming catastrophic forgetting with unlabeled data in the wild
Kibok Lee, Kimin Lee, Jinwoo Shin, and Honglak Lee · 2019
Cited alongside, same era.
Uncertainty-based continual learning with adaptive regularization
Hongjoon Ahn, Sungmin Cha, Donggyu Lee, and Taesup Moon · 2019
Cited alongside, same era.
Efficient lifelong learning with a-gem
Arslan Chaudhry, Marc’Aurelio Ranzato, Marcus Rohrbach, and Mohamed Elhoseiny · 2019
Cited alongside, same era.
Learning a unified classifier incrementally via rebalancing
Saihui Hou, Xinyu Pan, Chen Change Loy, Zilei Wang, and Dahua Lin · 2019
Cited alongside, same era.
Large scale incremental learning
Yue Wu, Yinpeng Chen, Lijuan Wang, Yuancheng Ye, Zicheng Liu, Yandong Guo, and Yun Fu · 2019
Cited alongside, same era.
Davide Abati, Jakub Tomczak, Tijmen Blankevoort, Simone Calderara, Rita Cucchiara, and Ehteshami Bejnordi · 2020
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Generalisation guarantees for continual learning with orthogonal gradient descent
Mehdi Abbana Bennani, Thang Doan, and Masashi Sugiyama · 2020
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Mnemonics training: Multi-class incremental learning without forgetting
Yaoyao Liu, Yuting Su, An-An Liu, Bernt Schiele, and Qianru Sun · 2020
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Energy-based out-of-distribution detection
Weitang Liu, Xiaoyun Wang, John Owens, and Yixuan Li · 2020
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Supervised contrastive learning
Prannay Khosla, Piotr Teterwak, Chen Wang, Aaron Sarna, Yonglong Tian, Phillip Isola, Aaron Maschinot, Ce Liu, and Dilip Krishnan · 2020
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Hrn: A holistic approach to one class learning
Wenpeng Hu, Mengyu Wang, Qi Qin, Jinwen Ma, and Bing Liu · 2020
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What’s hidden in a randomly weighted neural network?
Vivek Ramanujan, Mitchell Wortsman, Aniruddha Kembhavi, Ali Farhadi, and Mohammad Rastegari · 2020
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Self-initiated open world learning for autonomous ai agents
Bing Liu, Eric Robertson, Scott Grigsby, and Sahisnu Mazumder · 2021
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Prototype augmentation and self-supervision for incremental learning
Fei Zhu, Xu-Yao Zhang, Chuang Wang, Fei Yin, and Cheng-Lin Liu · 2021
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Adaptive aggregation networks for class-incremental learning
Yaoyao Liu, Bernt Schiele, and Qianru Sun · 2021
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Co2l: Contrastive continual learning
Hyuntak Cha, Jaeho Lee, and Jinwoo Shin · 2021
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Der: Dynamically expandable representation for class incremental learning
Shipeng Yan, Jiangwei Xie, and Xuming He · 2021
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Posterior meta-replay for continual learning
Christian Henning, Maria Cervera, Francesco D’Angelo, Johannes Von Oswald, Regina Traber, Benjamin Ehret, Seijin Kobayashi, Benjamin F Grewe, and João Sacramento · 2021
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Continual learning in the teacher-student setup: Impact of task similarity
Sebastian Lee, Sebastian Goldt, and Andrew Saxe · 2021
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Rainbow memory: Continual learning with a memory of diverse samples
Jihwan Bang, Heesu Kim, YoungJoon Yoo, Jung-Woo Ha, and Jonghyun Choi · 2021
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Zero-shot out-of-distribution detection based on the pretrained model clip
Sepideh Esmaeilpour, Bing Liu, Eric Robertson, and Lei Shu · 2022
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Cmg: A class-mixed generation approach to out-of-distribution detection
Mengyu Wang, Yijia Shao, Haowei Lin, Wenpeng Hu, and Bing Liu · 2022
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Learning curves for continual learning in neural networks: Self-knowledge transfer and forgetting
Ryo Karakida and Shotaro Akaho · 2022
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Memory replay with data compression for continual learning
Liyuan Wang, Xingxing Zhang, Kuo Yang, Longhui Yu, Chongxuan Li, Lanqing Hong, Shifeng Zhang, Zhenguo Li, Yi Zhong, and Jun Zhu · 2022
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Online continual learning through mutual information maximization
Yiduo Guo, Bing Liu, and Dongyan Zhao · 2022
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Adaptive orthogonal projection for batch and online continual learning
Yiduo Guo, Wenpeng Hu, Dongyan Zhao, and Bing Liu · 2022
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A multi-head model for continual learning via out-of-distribution replay
Gyuhak Kim, Zixuan Ke, and Bing Liu · 2022
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Continual learning based on ood detection and task masking
Gyuhak Kim, Sepideh Esmaeilpour, Changnan Xiao, and Bing Liu · 2022
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