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Class incremental learning (CIL) is a challenging setting of continual learning, which learns a series of tasks sequentially.
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Catastrophic interference in connectionist networks: The sequential learning problem
Michael McCloskey and Neal J Cohen · 1989
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Variable kernel density estimation
George R Terrell and David W Scott · 1992
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Alex Krizhevsky, Geoffrey Hinton, et al · 2009
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Convolutional deep belief networks on cifar-10
Alex Krizhevsky and Geoff Hinton · 2010
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Tiny imagenet visual recognition challenge
Ya Le and Xuan Yang · 2015
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ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei · 2015
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Towards open set deep networks
Abhijit Bendale and Terrance E Boult · 2016
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Dropout as a bayesian approximation: Representing model uncertainty in deep learning
Yarin Gal and Zoubin Ghahramani · 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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A baseline for detecting misclassified and out-of-distribution examples in neural networks
Dan Hendrycks and Kevin Gimpel · 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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Expert gate: Lifelong learning with a network of experts
Rahaf Aljundi, Punarjay Chakravarty, and Tinne Tuytelaars · 2017
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Fearnet: Brain-inspired model for incremental learning
Ronald Kemker and Christopher Kanan · 2017
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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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Enhancing the reliability of out-of-distribution image detection in neural networks
Shiyu Liang, Yixuan Li, and Rayadurgam Srikant · 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, Georg Sperl, and Christoph H Lampert · 2017
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End-to-end incremental learning
Francisco M Castro, Manuel J Marín-Jiménez, Nicolás Guil, Cordelia Schmid, and Karteek Alahari · 2018
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Efficient lifelong learning with a-gem
Arslan Chaudhry, Marc’Aurelio Ranzato, Marcus Rohrbach, and Mohamed Elhoseiny · 2018
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Deep anomaly detection with outlier exposure
Dan Hendrycks, Mantas Mazeika, and Thomas Dietterich · 2018
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Packnet: Adding multiple tasks to a single network by iterative pruning
Arun Mallya and Svetlana Lazebnik · 2018
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Do deep generative models know what they don’t know?
Eric Nalisnick, Akihiro Matsukawa, Yee Whye Teh, Dilan Gorur, and Balaji Lakshminarayanan · 2018
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Overcoming catastrophic forgetting with hard attention to the task
Joan Serra, Didac Suris, Marius Miron, and Alexandros Karatzoglou · 2018
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Scaling out-of-distribution detection for real-world settings
Dan Hendrycks, Steven Basart, Mantas Mazeika, Mohammadreza Mostajabi, Jacob Steinhardt, and Dawn Song · 2019
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Parameter-efficient transfer learning for nlp
Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin De Laroussilhe, Andrea Gesmundo, Mona Attariyan, and Sylvain Gelly · 2019
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Overcoming catastrophic forgetting with unlabeled data in the wild
Kibok Lee, Kimin Lee, Jinwoo Shin, and Honglak Lee · 2019
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On mixup training: Improved calibration and predictive uncertainty for deep neural networks
Sunil Thulasidasan, Gopinath Chennupati, Jeff A Bilmes, Tanmoy Bhattacharya, and Sarah Michalak · 2019
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Continual learning with hypernetworks
Johannes Von Oswald, Christian Henning, Benjamin F Grewe, and João Sacramento · 2019
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Pytorch image models
Ross Wightman · 2019
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Ternary feature masks: zero-forgetting for task-incremental learning
Marc Masana, Tinne Tuytelaars, and Joost Van de Weijer · 2021
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React: Out-of-distribution detection with rectified activations
Yiyou Sun, Chuan Guo, and Yixuan Li · 2021
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Training data-efficient image transformers & distillation through attention
Hugo Touvron, Matthieu Cord, Matthijs Douze, Francisco Massa, Alexandre Sablayrolles, and Hervé Jégou · 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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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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Online continual learning on a contaminated data stream with blurry task boundaries
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Sangdoo Yun, Dongyoon Han, Seong Joon Oh, Sanghyuk Chun, Junsuk Choe, and Youngjoon Yoo · 2019
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Continual learning of context-dependent processing in neural networks
Guanxiong Zeng, Yang Chen, Bo Cui, and Shan Yu · 2019
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Conditional channel gated networks for task-aware continual learning
Davide Abati, Jakub Tomczak, Tijmen Blankevoort, Simone Calderara, Rita Cucchiara, and Babak Ehteshami Bejnordi · 2020
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Dark experience for general continual learning: a strong, simple baseline
Pietro Buzzega, Matteo Boschini, Angelo Porrello, Davide Abati, and Simone Calderara · 2020
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Compositional visual generation with energy based models
Yilun Du, Shuang Li, and Igor Mordatch · 2020
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Embracing change: Continual learning in deep neural networks
Raia Hadsell, Dushyant Rao, Andrei A Rusu, and Razvan Pascanu · 2020
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Lifelong machine learning with deep streaming linear discriminant analysis
Tyler L Hayes and Christopher Kanan · 2020
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Jihwan Bang, Hyunseo Koh, Seulki Park, Hwanjun Song, Jung-Woo Ha, and Jonghyun Choi · 2022
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Consistency is the key to further mitigating catastrophic forgetting in continual learning
Prashant Bhat, Bahram Zonooz, and E. Arani · 2022
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Online continual learning through mutual information maximization
Yiduo Guo, Bing Liu, and Dongyan Zhao · 2022
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Class-incremental learning by knowledge distillation with adaptive feature consolidation
Minsoo Kang, Jaeyoo Park, and Bohyung Han · 2022
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Continual learning of natural language processing tasks: A survey
Zixuan Ke and Bing Liu · 2022
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Continual few-shot intent detection
Guodun Li, Yuchen Zhai, Qianglong Chen, Xing Gao, Ji Zhang, and Yin Zhang · 2022
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Out-of-distribution detection with deep nearest neighbors
Yiyou Sun, Yifei Ming, Xiaojin Zhu, and Yixuan Li · 2022
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Open-set recognition: A good closed-set classifier is all you need?
S Vaze, K Han, A Vedaldi, and A Zisserman · 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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Mitigating neural network overconfidence with logit normalization
Hongxin Wei, Renchunzi Xie, Hao Cheng, Lei Feng, Bo An, and Yixuan Li · 2022
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Openood: Benchmarking generalized out-of-distribution detection
Jingkang Yang, Pengyun Wang, Dejian Zou, Zitang Zhou, Kunyuan Ding, Wenxuan Peng, Haoqi Wang, Guangyao Chen, Bo Li, Yiyou Sun, Xuefeng Du, Kaiyang Zhou, Wayne Zhang, Dan Hendrycks, Yixuan Li, and Ziwei Liu · 2022
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Dealing with cross-task class discrimination in online continual learning
Yiduo Guo, Bing Liu, and Dongyan Zhao · 2023
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Birt: Bio-inspired replay in vision transformers for continual learning
Kishaan Jeeveswaran, Prashant Bhat, Bahram Zonooz, and E. Arani · 2023
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Continual pre-training of language models
Zixuan Ke, Yijia Shao, Haowei Lin, Tatsuya Konishi, Gyuhak Kim, and Bing Liu · 2023
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Learnability and algorithm for continual learning
Gyuhak Kim, Changnan Xiao, Tatsuya Konishi, and Bing Liu · 2023
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Flats: Principled out-of-distribution detection with feature-based likelihood ratio score
Haowei Lin and Yuntian Gu · 2023
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Class-incremental learning based on label generation
Yijia Shao, Yiduo Guo, Dongyan Zhao, and Bing Liu · 2023
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A comprehensive survey of continual learning: Theory, method and application, 2023
Liyuan Wang, Xingxing Zhang, Hang Su, and Jun Zhu · 2023
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Tkil: Tangent kernel optimization for class balanced incremental learning
Jinlin Xiang and Eli Shlizerman · 2023
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Mixture outlier exposure: Towards out-of-distribution detection in fine-grained environments
Jingyang Zhang, Nathan Inkawhich, Randolph Linderman, Yiran Chen, and Hai Li · 2023
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Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan, and Ziwei Liu · 2023
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