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Artificial learning systems aspire to mimic human intelligence by continually learning from a stream of tasks without forgetting past knowledge.
Catastrophic interference in connectionist networks: The sequential learning problem
Michael Mccloskey and Neil J. Cohen · 1989
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Connectionist models of recognition memory: constraints imposed by learning and forgetting functions
Roger Ratcliff · 1990
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Catastrophic forgetting, rehearsal and pseudorehearsal
Anthony V. Robins · 1995
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Lifelong robot learning
Sebastian Thrun and Tom M. Mitchell · 1995
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Child: A first step towards continual learning
Mark B. Ring · 1998
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Learning multiple layers of features from tiny images
Alex Krizhevsky · 2009
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P. Welinder, S. Branson, T. Mita, C. Wah, F. Schroff, S. Belongie, and P. Perona · 2010
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Deep inside convolutional networks: Visualising image classification models and saliency maps
Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman · 2014
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Deep networks for saliency detection via local estimation and global search
Lijun Wang, Huchuan Lu, Xiang Ruan, and Ming-Hsuan Yang · 2015
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Saliency detection by multi-context deep learning
Rui Zhao, Wanli Ouyang, Hongsheng Li, and Xiaogang Wang · 2015
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Deep learning
Ian Goodfellow, Yoshua Bengio, Aaron Courville, and Yoshua Bengio · 2016
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Visualizing deep convolutional neural networks using natural pre-images
Aravindh Mahendran and Andrea Vedaldi · 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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Matching networks for one shot learning
Oriol Vinyals, Charles Blundell, Timothy Lillicrap, Koray Kavukcuoglu, and Daan Wierstra · 2016
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Learning deep features for discriminative localization
Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, and Antonio Torralba · 2016
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Overcoming catastrophic forgetting in neural networks
James Kirkpatrick, Razvan Pascanu, Neil C. Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A. Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, Demis Hassabis, Claudia Clopath, Dharshan Kumaran, and Raia Hadsell · 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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Grad-CAM: Visual explanations from deep networks via gradient-based localization
Ramprasaath R. Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra · 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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SmoothGrad: removing noise by adding noise
Daniel Smilkov, Nikhil Thorat, Been Kim, Fernanda Viégas, and Martin Wattenberg · 2017
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Continual learning through synaptic intelligence
Friedemann Zenke, Ben Poole, and Surya Ganguli · 2017
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Peeking inside the black-box: A survey on explainable artificial intelligence (XAI)
Amina Adadi and Mohammed Berrada · 2018
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Memory aware synapses: Learning what (not) to forget
Rahaf Aljundi, Francesca Babiloni, Mohamed Elhoseiny, Marcus Rohrbach, and Tinne Tuytelaars · 2018
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Grad-CAM++: Generalized gradient-based visual explanations for deep convolutional networks
Learning to learn without forgetting by maximizing transfer and minimizing interference
Matthew Riemer, Ignacio Cases, Robert Ajemian, Miao Liu, Irina Rish, Yuhai Tu, and Gerald Tesauro · 2019
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Experience replay for continual learning
David Rolnick, Arun Ahuja, Jonathan Schwarz, Timothy Lillicrap, and Gregory Wayne · 2019
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Full-gradient representation for neural network visualization
Suraj Srinivas and François Fleuret · 2019
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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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Online continual learning from imbalanced data
Aristotelis Chrysakis and Marie-Francine Moens · 2020
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Adversarial continual learning
Sayna Ebrahimi, Franziska Meier, Roberto Calandra, Trevor Darrell, and Marcus Rohrbach · 2020
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Aditya Chattopadhay, Anirban Sarkar, Prantik Howlader, and Vineeth N Balasubramanian · 2018
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Re-evaluating continual learning scenarios: A categorization and case for strong baselines
Yen-Chang Hsu, Yen-Cheng Liu, Anita Ramasamy, and Zsolt Kira · 2018
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Learning without forgetting
Zhizhong Li and Derek Hoiem · 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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Variational continual learning
Cuong V. Nguyen, Yingzhen Li, Thang D. Bui, and Richard E. Turner · 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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Lifelong learning with dynamically expandable networks
Jaehong Yoon, Eunho Yang, Jeongtae Lee, and Sung Ju Hwang · 2018
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Orthogonal gradient descent for continual learning
Mehrdad Farajtabar, Navid Azizan, Alex Mott, and Ang Li · 2020
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Improved schemes for episodic memory-based lifelong learning
Yunhui Guo, Mingrui Liu, Tianbao Yang, and Tajana Rosing · 2020
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Optimal continual learning has perfect memory and is np-hard
Jeremias Knoblauch, H. Husain, and Tom Diethe · 2020
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Gdumb: A simple approach that questions our progress in continual learning
Ameya Prabhu, Philip Torr, and Puneet Dokania · 2020
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Using hindsight to anchor past knowledge in continual learning
Arslan Chaudhry, Albert Gordo, Puneet K Dokania, Philip HS Torr, and David Lopez-Paz · 2021
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Continual prototype evolution: Learning online from non-stationary data streams
Matthias De Lange and Tinne Tuytelaars · 2021
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A continual learning survey: Defying forgetting in classification tasks
M. Delange, R. Aljundi, M. Masana, S. Parisot, X. Jia, A. Leonardis, G. Slabaugh, and T. Tuytelaars · 2021
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Remembering for the right reasons: Explanations reduce catastrophic forgetting
Sayna Ebrahimi, Suzanne Petryk, Akash Gokul, William Gan, Joseph E. Gonzalez, Marcus Rohrbach, and trevor darrell · 2021
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SPACE: Structured compression and sharing of representational space for continual learning
Gobinda Saha, Isha Garg, Aayush Ankit, and Kaushik Roy · 2021
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Gradient projection memory for continual learning
Gobinda Saha, Isha Garg, and Kaushik Roy · 2021
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Online class-incremental continual learning with adversarial shapley value
Dongsub Shim, Zheda Mai, Jihwan Jeong, Scott Sanner, Hyunwoo Kim, and Jongseong Jang · 2021
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Rehearsal revealed: The limits and merits of revisiting samples in continual learning
Eli Verwimp, Matthias De Lange, and Tinne Tuytelaars · 2021
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Online continual learning in image classification: An empirical survey
Zheda Mai, Ruiwen Li, Jihwan Jeong, David Quispe, Hyunwoo Kim, and Scott Sanner · 2022
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