Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence

Deep Residual Learning for Image Recognition

He, K., Zhang, X., Ren, S., & Sun, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.90 · Cited by 235,474

Adam: A Method for Stochastic Optimization

Kingma, D. P., & Ba, J. (2014) · arXiv · doi:10.48550/arxiv.1412.6980 · Cited by 98,946

Learning Multiple Layers of Features from Tiny Images

Krizhevsky, A. (2024) · doi:10.57702/zp44cu3g · Cited by 23,889

On Information and Sufficiency

Kullback, S., & Leibler, R. A. (1951) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177729694 · Cited by 20,193

Distilling the Knowledge in a Neural Network

Hinton, G., Vinyals, O., & Dean, J. (2015) · arXiv · doi:10.48550/arxiv.1503.02531 · Cited by 14,204

Overcoming catastrophic forgetting in neural networks

Kirkpatrick, J., Pascanu, R., Rabinowitz, N., Veness, J., Desjardins, G., Rusu, A. A., Milan, K., Quan, J., Ramalho, T., Grabska-Barwinska, A., et al. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1611835114 · Cited by 7,899

Deep Residual Learning for Image Recognition

He, K., Zhang, X., Ren, S., & Sun, J. (2015) · arXiv · doi:10.48550/arxiv.1512.03385 · Cited by 4,196

iCaRL: Incremental Classifier and Representation Learning

Rebuffi, S.-A., Kolesnikov, A., Sperl, G., & Lampert, C. H. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.587 · Cited by 3,988

Natural Gradient Works Efficiently in Learning

Амари, Ш.-И. (1998) · Neural Computation · doi:10.1162/089976698300017746 · Cited by 2,914

Theory of the backpropagation neural network

Hecht-Nielsen (1989) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.1989.118638 · Cited by 2,274

Transmitter Identification With Contrastive Learning in Incremental Open-Set Recognition

Zhang, X., Huang, Y., Lin, M., Tian, Y., & An, J. (2023) · IEEE Internet of Things Journal · doi:10.1109/jiot.2023.3300122 · Cited by 13

Domain-incremental learning without forgetting based on random vector functional link networks

Liu, C., Wang, Y., Li, D., & Wang, X. (2024) · Pattern Recognition · doi:10.1016/j.patcog.2024.110430 · Cited by 13

Bridging pre-trained models to continual learning: A hypernetwork based framework with parameter-efficient fine-tuning techniques

Ding, F., Xu, C. G., Liu, H., Zhou, B., & Zhou, H. (2024) · Information Sciences · doi:10.1016/j.ins.2024.120710 · Cited by 14

Class Incremental Learning for Light-Weighted Networks

Tao, Z., Yu, L., Yao, H., Huang, S., & Xu, C. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3424302 · Cited by 13

Balanced Destruction-Reconstruction Dynamics for Memory-Replay Class Incremental Learning

Zhou, Y., Yao, J., Hong, F., Zhang, Y., & Wang, Y. (2024) · IEEE Transactions on Image Processing · doi:10.1109/tip.2024.3451932 · Cited by 19

Learning Equi-Angular Representations for Online Continual Learning

Seo, M., Koh, H., Jeung, W., Lee, M., Kim, S., Lee, H., Cho, S., Choi, S., Kim, H., & Choi, J. (2024) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52733.2024.02259 · Cited by 13

CEAT: Continual Expansion and Absorption Transformer for Non-Exemplar Class-Incremental Learning

Dong, S., Gao, X., He, Y., Zhou, Z., Kot, A. C., & Gong, Y. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3502837 · Cited by 13

The role of lifelong machine learning in bridging the gap between human and machine learning: A scientometric analysis

Abulaish, M., Wasi, N. A., & Sharma, S. (2024) · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · doi:10.1002/widm.1526 · Cited by 13

Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning

Szatkowski, F., Pyla, M., Przewięźlikowski, M., Cygert, S., Twardowski, B., & Trzcinski, T. P. (2024) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv57701.2024.00198 · Cited by 16

SERIL: Noise Adaptive Speech Enhancement Using Regularization-Based Incremental Learning

Lee, C.-C., Lin, Y.-C., Lin, H.-T., Wang, H., & Tsao, Y. (2020) · Interspeech (USB) · doi:10.21437/interspeech.2020-2213 · Cited by 13

Continual Information Cascade Learning

Zhou, F., Jing, X., Xu, X., Zhong, T., Trajcevski, G., & Wu, J. (2020) · Globecom · doi:10.1109/globecom42002.2020.9322124 · Cited by 13

Continuous Coordination As a Realistic Scenario for Lifelong LearningPreprint

Nekoei, H., Badrinaaraayanan, A., Courville, A. C., & Chandar, S. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2103.03216 · Cited by 17

Learnable Expansion-and-Compression Network for Few-shot Class-Incremental LearningPreprint

Yang, B., Lin, M., Liu, B., Fu, M., Liu, C., Ji, R., & Ye, Q. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2104.02281 · Cited by 13

Prototype-based Incremental Few-Shot Semantic SegmentationPreprint

Cermelli, F., Mancini, M., Xian, Y., Akata, Z., & Barbara Caputo, B. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2012.01415 · Cited by 13

Beyond Reptile: Meta-Learned Dot-Product Maximization between Gradients for Improved Single-Task Regularization

Kedia, A., Chinthakindi, S. C., & Ryu, W. (2021) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2021.findings-emnlp.37 · Cited by 14

Topology-Aware Graph Convolution Network for Few-Shot Incremental 3-D Object Learning

Ma, B., Cong, Y., & Dong, J. (2023) · IEEE Transactions on Systems Man and Cybernetics Systems · doi:10.1109/tsmc.2023.3302008 · Cited by 12

Chameleon: Dual Memory Replay for Online Continual Learning on Edge Devices

Aggarwal, S., Binici, K., & Mitra, T. (2023) · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · doi:10.1109/tcad.2023.3347640 · Cited by 12

Improving Plasticity in Online Continual Learning via Collaborative Learning

Wang, M., Michel, N., Xiao, L., & Yamasaki, T. (2024) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52733.2024.02214 · Cited by 16

Continual Learning Through Human-Robot Interaction: Human Perceptions of a Continual Learning Robot in Repeated Interactions

Ayub, A., Francesco, Z. D., Holthaus, P., Nehaniv, C. L., & Dautenhahn, K. (2025) · International Journal of Social Robotics · doi:10.1007/s12369-025-01214-9 · Cited by 12

MuseumMaker: Continual Style Customization Without Catastrophic Forgetting

Liu, C., Sun, G., Liang, W., Dong, J., Qin, C., & Cong, Y. (2025) · IEEE Transactions on Image Processing · doi:10.1109/tip.2025.3553024 · Cited by 16

Feature space expansion and compression with spatial–spectral augmentation for hyperspectral image Class-Incremental Learning

Wu, R., Liu, H., Yue, Z., Sham, C., & Li, J. (2025) · Pattern Recognition · doi:10.1016/j.patcog.2025.111830 · Cited by 12

Deep Virtual Networks for Memory Efficient Inference of Multiple Tasks

Kim, E., Ahn, C., Torr, P. H. S., & Oh, S. (2019) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2019.00282 · Cited by 12

Regression Bugs Are In Your Model! Measuring, Reducing and Analyzing Regressions In NLP Model Updates

Xie, Y., Lai, Y.-A., Xiong, Y., Zhang, Y., & Soatto, S. (2021) · doi:10.18653/v1/2021.acl-long.515 · Cited by 19

Continual Learning with Dual Regularizations

Han, X., & Guo, Y. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-86486-6_38 · Cited by 12

Prompt Augmented Generative Replay via Supervised Contrastive Learning for Lifelong Intent Detection

Varshney, V., Patidar, M., Kumar, R., Vig, L., & Shroff, G. M. (2022) · Findings of the Association for Computational Linguistics: NAACL · doi:10.18653/v1/2022.findings-naacl.84 · Cited by 12

Adaptive Online Domain Incremental Continual Learning

Gunasekara, N., Gomes, H. M., Bifet, A., & Pfahringer, B. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-15919-0_41 · Cited by 12

Task-Agnostic Continual Hippocampus Segmentation for Smooth Population Shifts

González, C., Ranem, A., Othman, A. E., & Mukhopadhyay, A. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-16852-9_11 · Cited by 12

Improving Replay-Based Continual Semantic Segmentation with Smart Data Selection

Kalb, T., Mauthe, B., & Beyerer, J. (2022) · IEEE International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc55140.2022.9922284 · Cited by 13

Prompt Conditioned VAE: Enhancing Generative Replay for Lifelong Learning in Task-Oriented Dialogue

Zhao, Y., Zheng, Y., Tian, Z., Gao, C., Sun, J., & Zhang, N. L. (2022) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2022.emnlp-main.766 · Cited by 14

On the Usage of Continual Learning for Out-of-Distribution Generalization in Pre-trained Language Models of Code

Weyssow, M., Zhou, X., Kim, K., Lo, D., & Sahraoui, H. A. (2023) · ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) · doi:10.1145/3611643.3616244 · Cited by 16

TKIL: Tangent Kernel Optimization for Class Balanced Incremental Learning

Xiang, J., & Shlizerman, E. (2023) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw60793.2023.00379 · Cited by 12

MEIL-NeRF: Memory-Efficient Incremental Learning of Neural Radiance Fields

Chung, J., Lee, K., Baik, S., & Lee, K. M. (2025) · IEEE Access · doi:10.1109/access.2025.3578393 · Cited by 14

OvA-INN: Continual Learning with Invertible Neural Networks

Hocquet, G., Bichler, O., & Querlioz, D. (2020) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn48605.2020.9206766 · Cited by 15

Generative Replay-Based Continual Zero-Shot Learning

Gautam, C., Parameswaran, S., Mishra, A., & Sundaram, S. (2024) · WORLD SCIENTIFIC eBooks · doi:10.1142/9789811286711_0005 · Cited by 13

Effect of Pruning on Catastrophic Forgetting in Growing Dual Memory Networks

Liew, W. S., Loo, C. K., Gryshchuk, V., Weber, C., & Wermter, S. (2019) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2019.8851865 · Cited by 12

Half-Real Half-Fake Distillation for Class-Incremental Semantic SegmentationPreprint

Huang, Z., Hao, W., Wang, X., Tao, M., Huang, J., Liu, W., & Hua, X. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2104.00875 · Cited by 12

Trust-Region Adaptive Frequency for Online Continual Learning

Kong, Y., Liu, L., Qiao, M., Wang, Z., & Tao, D. (2023) · International Journal of Computer Vision · doi:10.1007/s11263-023-01775-0 · Cited by 11

Continual text classification based on knowledge distillation and class-aware experience replay

Yang, F., Che, Y., Kang, M., Liu, S., & Fu, Z. (2023) · Knowledge and Information Systems · doi:10.1007/s10115-023-01889-4 · Cited by 11

Measuring Asymmetric Gradient Discrepancy in Parallel Continual Learning

Lyu, F., Sun, Q., Shang, F., Wan, L., & Feng, W. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.01048 · Cited by 11

SCREAM: Knowledge sharing and compact representation for class incremental learning

Feng, Z., Zhou, M., Gao, Z., Stefanidis, A., & Sui, Z. (2024) · Information Processing & Management · doi:10.1016/j.ipm.2023.103629 · Cited by 11

CL-BPUWM: continuous learning with Bayesian parameter updating and weight memory

He, Y., Yang, J., Li, S., Hu, J., Ren, Y., & Ji, Q. (2024) · Complex & Intelligent Systems · doi:10.1007/s40747-024-01350-1 · Cited by 11

Hyper-feature aggregation and relaxed distillation for class incremental learning

Wu, R., Liu, H., Yue, Z., Li, J., & Sham, C. (2024) · Pattern Recognition · doi:10.1016/j.patcog.2024.110440 · Cited by 11

MICIL: Multiple-Instance Class-Incremental Learning for skin cancer whole slide images

Meseguer, P., del Amor, R., & Naranjo, V. (2024) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2024.102870 · Cited by 11

APM: Adaptive parameter multiplexing for class incremental learning

Gao, J., Xie, T., Li, R., Wang, K., & Zhao, L.-J. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.125135 · Cited by 12

A masking, linkage and guidance framework for online class incremental learning

Liang, G., Chen, Z., Su, S., Zhang, S., & Zhang, Y. (2024) · Pattern Recognition · doi:10.1016/j.patcog.2024.111185 · Cited by 12

Achieving Plasticity-Stability Trade-Off in Continual Learning Through Adaptive Orthogonal Projection

Cheng, D., Hu, Y., Wang, N., Zhang, D., & Gao, X. (2025) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2025.3547916 · Cited by 11

Rethinking Knowledge Distillation in Collaborative Machine Learning: Memory, Knowledge, and Their Interactions

Han, P., Huang, X., Fang, Y., & Han, G. (2025) · IEEE Transactions on Network Science and Engineering · doi:10.1109/tnse.2025.3572362 · Cited by 11

LLM-ACNC: Aerospace Requirement Texts Knowledge Graph Construction Utilizing Large Language Model

Liu, Y., Hou, J., Chen, Y., Jin, J., & Wang, W. (2025) · Aerospace · doi:10.3390/aerospace12060463 · Cited by 12

A layer-specific constraint-based enriched physics-informed neural network for solving two-phase flow problems in heterogeneous porous media

Lin, J.-Q., Yan, X., Wang, E.-Z., Zhang, Q., Zhang, K., Liu, P., & Zhang, L. (2025) · Petroleum Science · doi:10.1016/j.petsci.2025.07.008 · Cited by 13

Online deep learning based on auto-encoder

Zhang, S., Liu, J., Zuo, X., Lu, R., & Lian, S.-M. (2021) · Applied Intelligence · doi:10.1007/s10489-020-02058-8 · Cited by 11

Incorporating geometry knowledge into an incremental learning structure for few-shot intent recognition

Zhang, X., Jiang, M., Chen, H., Zheng, J., & Pan, Z. (2022) · Knowledge-Based Systems · doi:10.1016/j.knosys.2022.109296 · Cited by 11

Towards Continual Social Network Identification

Magistri, S., Baracchi, D., Shullani, D., Bagdanov, A. D., & Piva, A. (2023) · International Workshop on Biometrics and Forensics (IWBF) · doi:10.1109/iwbf57495.2023.10157835 · Cited by 11

A Multi-Class Intrusion Detection System Based on Continual Learning

Oikonomou, C., Iliopoulos, I., Ioannidis, D., & Tzovaras, D. K. (2023) · IEEE International Conference on Cyber Security and Resilience (CSR) · doi:10.1109/csr57506.2023.10224974 · Cited by 11

Lifelong ensemble learning based on multiple representations for few-shot object recognition

Kasaei, H., & Xiong, S. (2024) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2023.104615 · Cited by 11

Plasticity-Optimized Complementary Networks for Unsupervised Continual Learning

Gomez-Villa, A., Twardowski, B., Wang, K., & van de Weijer, J. (2024) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv57701.2024.00171 · Cited by 14

Select and Distill: Selective Dual-Teacher Knowledge Transfer for Continual Learning on Vision-Language Models

Yu, Y.-C., Huang, C.-P., Chen, J. C., Chang, K.-P., Lai, Y.-H., Yang, F.-E., & Wang, Y.-C. F. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-73347-5_13 · Cited by 12

Simple Lifelong Learning Machines

Vogelstein, J. T., Dey, J. K., Helm, H. S., LeVine, W., Mehta, R., Tomita, T. M., Xu, H., Geisa, A., Wang, Q., van de Ven, G. M., et al. (2025) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2025.3595364 · Cited by 26

Learning Then, Learning Now, and Every Second in Between: Lifelong Learning With a Simulated Humanoid Robot

Logacjov, A., Kerzel, M., & Wermter, S. (2021) · Frontiers in Neurorobotics · doi:10.3389/fnbot.2021.669534 · Cited by 11

On Class Orderings for Incremental LearningPreprint

Masana, M., Twardowski, B., & van de Weijer, J. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2007.02145 · Cited by 11

Storing Encoded Episodes as Concepts for Continual LearningPreprint

Ayub, A., & Wagner, A. R. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2007.06637 · Cited by 11

On the importance of cross-task features for class-incremental learningPreprint

Soutif--Cormerais, A., Masana, M., van de Weijer, J., & Twardowski, B. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2106.11930 · Cited by 11

Relationship-Incremental Scene Graph Generation by a Divide-and-Conquer Pipeline With Feature Adapter

Li, X., Zheng, G., Yu, Y., Ji, N., & Li, X. (2024) · IEEE Transactions on Image Processing · doi:10.1109/tip.2024.3384096 · Cited by 10

FedINC: An Exemplar-Free Continual Federated Learning Framework with Small Labeled Data

Deng, Y., Yue, S., Wang, T., Wang, G. Y., Ren, J., & Zhang, Y. (2023) · ACM Conference on Embedded Networked Sensor Systems (SenSys) · doi:10.1145/3625687.3625800 · Cited by 10

Online industrial fault prognosis in dynamic environments via task-free continual learning

Liu, C., Zhang, L., Zheng, Y., Jiang, Z., Zheng, J., & Wu, C. (2024) · Neurocomputing · doi:10.1016/j.neucom.2024.127930 · Cited by 10

Advancing continual lifelong learning in neural information retrieval: Definition, dataset, framework, and empirical evaluation

Hou, J., Cosma, G., & Finke, A. (2024) · Information Sciences · doi:10.1016/j.ins.2024.121368 · Cited by 10

TAME: Task Agnostic Continual Learning using Multiple Experts

Zhu, H., Majzoubi, M., Jain, A., & Choromanska, A. (2024) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw63382.2024.00417 · Cited by 13

CoLeCLIP: Open-Domain Continual Learning via Joint Task Prompt and Vocabulary Learning

Li, Y., Pang, G., Suo, W., Jing, C., Xi, Y., Liu, L., Chen, H., Liang, G., & Wang, P. (2025) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2025.3547882 · Cited by 10

Effective Generative Replay with Strong Memory for Continual Learning

Yang, J., Zhou, X., He, Y., Li, Q., Su, Z., Ruan, X., & Zhang, C. (2025) · Knowledge-Based Systems · doi:10.1016/j.knosys.2025.113477 · Cited by 10

Federated continual learning for task-incremental and class-incremental problems: A survey

Birashk, A., & Khan, L. R. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.129278 · Cited by 10

Prioritized Experience Replay for Continual Learning

Hu, G., Zhang, W., & Zhu, W. (2021) · International Conference on Computational Intelligence and Applications (ICCIA) · doi:10.1109/iccia52886.2021.00011 · Cited by 11

Rainbow Keywords: Efficient Incremental Learning for Online Spoken Keyword Spotting

Yang, X., Hou, N., & Chng, E. S. (2022) · Interspeech (USB) · doi:10.21437/interspeech.2022-10500 · Cited by 10

Target layer regularization for continual learning using Cramer-Wold distance

Mazur, M., Pustelnik, Ł., Knop, S., Pagacz, P., & Spurek, P. (2022) · Information Sciences · doi:10.1016/j.ins.2022.07.085 · Cited by 10

Continuous cross-modal hashing

Zheng, H., Wang, J., Zhen, X., Song, J., Zheng, F., Lü, K., & Qi, G.-J. (2023) · Pattern Recognition · doi:10.1016/j.patcog.2023.109662 · Cited by 10

Incremental Fault Diagnosis Method Based on Metric Feature Distillation and Improved Sample Memory

Min, Q., He, J., Yu, P., & Fu, Y. (2023) · IEEE Access · doi:10.1109/access.2023.3274481 · Cited by 10

Online Continual Learning for Robust Indoor Object Recognition

Michieli, U., & Özay, M. (2023) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros55552.2023.10341474 · Cited by 10

On the Effectiveness of LayerNorm Tuning for Continual Learning in Vision Transformers

Min, T. D., Mancini, M., Alahari, K., Alameda-Pineda, X., & Ricci, E. (2023) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw60793.2023.00385 · Cited by 12

Rapid Adaptation in Online Continual Learning: Are We Evaluating It Right?

Hammoud, H. A. A. K., Prabhu, A., Lim, S.-N., Torr, P. H. S., Bibi, A., & Ghanem, B. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.01728 · Cited by 10

Incremental Scene Classification Using Dual Knowledge Distillation and Classifier Discrepancy on Natural and Remote Sensing Images

Yu, C.-C., Chen, T.-Y., Hsu, C.-W., & Cheng, H.-Y. (2024) · Electronics · doi:10.3390/electronics13030583 · Cited by 10

Enhance Adversarial Robustness via Geodesic Distance

Yan, J., Yin, H., Zhao, Z., Wan-cheng, G., & Zhang, J. (2024) · IEEE Transactions on Artificial Intelligence · doi:10.1109/tai.2024.3364121 · Cited by 11

Continual atlas-based segmentation of prostate MRI

Ranem, A., González, C., dos Santos, D. P., Bucher, A. M., Othman, A. E., & Mukhopadhyay, A. (2024) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv57701.2024.00739 · Cited by 10

Class Balance Matters to Active Class-Incremental Learning

Huang, Z., Chen, Z., Li, Y., Dong, B., Zhou, E., Liu, Y., Goh, R. S. M., Feng, C.-M., & Zuo, W. (2024) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3664647.3680822 · Cited by 12

ARCADe: A Rapid Continual Anomaly Detector

Frikha, A., Krompaß, D., & Tresp, V. (2021) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr48806.2021.9412627 · Cited by 10

Continual Domain Adaptation for Machine Reading Comprehension

Su, L., Guo, J., Zhang, R., Fan, Y., Lan, Y., & Cheng, X. (2020) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3340531.3412047 · Cited by 10

Alleviating Representational Shift for Continual Fine-tuning

Jie, S., Deng, Z., & Li, Z. (2022) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw56347.2022.00426 · Cited by 11

Variational Auto-Regressive Gaussian Processes for Continual LearningPreprint

Kapoor, S., Karaletsos, T., & Bui, T. D. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2006.05468 · Cited by 10

Zero-exemplar deep continual learning for crop disease recognition: a study of total variation attention regularization in vision transformers

Wang, B. (2024) · Frontiers in Plant Science · doi:10.3389/fpls.2023.1283055 · Cited by 9

Hierarchical Augmentation and Distillation for Class Incremental Audio-Visual Video Recognition

Zuo, Y., Yao, H., Zhuang, L., & Xu, C. (2024) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2024.3387946 · Cited by 10

Latent spectral regularization for continual learning

Frascaroli, E., Benaglia, R., Boschini, M., Moschella, L., Fiorini, C., Rodolà, E., & Calderara, S. (2024) · Pattern Recognition Letters · doi:10.1016/j.patrec.2024.06.020 · Cited by 9

Conditioned Prompt-Optimization for Continual Deepfake Detection

Laiti, F., Liberatori, B., Min, T. D., & Ricci, E. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-78189-6_5 · Cited by 9

FPPL: An Efficient and Non-IID Robust Federated Continual Learning Framework

He, Y., Shen, C., Wang, X., & Jin, B. (2024) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata62323.2024.10825220 · Cited by 9

Federated Continual Learning Based on Weakly Supervised Diffusion Models for Disease Diagnosis

Sun, H., Zhang, W., Zhang, R., Xu, L., Guan, H., Zhao, H., Zhang, B., Yang, S., & Xin, Y. (2025) · IEEE Internet of Things Journal · doi:10.1109/jiot.2025.3535628 · Cited by 9

Efficient Training of Neural Network Potentials for Chemical and Enzymatic Reactions by Continual Learning

Lei, Y.-K., Yagi, K., & Sugita, Y. (2025) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.4c01393 · Cited by 9

HyperKD: Lifelong Hyperspectral Image Classification With Cross-Spectral–Spatial Knowledge Distillation

Li, Z., Xia, S., Yue, J., & Fang, L. (2025) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2025.3552449 · Cited by 9

New Generation Federated Learning

Li, B., Chen, S., & Peng, Z. (2022) · Sensors · doi:10.3390/s22218475 · Cited by 11

Rectification-Based Knowledge Retention for Task Incremental Learning

Mazumder, P., Singh, P. P., Rai, P., & Namboodiri, V. P. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2022.3225310 · Cited by 9

Few-Shot Incremental Learning for Label-to-Image Translation

Chen, P., Zhang, Y., Li, Z., & Sun, L. (2022) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52688.2022.00368 · Cited by 9

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Alssum, L., Alcázar, J. L., Ramazanova, M., Zhao, C., & Ghanem, B. (2023) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw59228.2023.00246 · Cited by 9

Online Distillation with Continual Learning for Cyclic Domain Shifts

Houyon, J., Cioppa, A., Ghunaim, Y., Alfarra, M., Halin, A., Henry, M., Ghanem, B., & Droogenbroeck, M. V. (2023) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw59228.2023.00242 · Cited by 9

Slow-Fast Time Parameter Aggregation Network for Class-Incremental Lip Reading

Zhang, X., Zhang, C., Wang, T., Tang, J., Lao, S., & Li, H. (2023) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3581783.3612460 · Cited by 9

Contrastive Continuity on Augmentation Stability Rehearsal for Continual Self-Supervised Learning

Cheng, H., Wen, H., Zhang, X., Qiu, H., Wang, L., & Li, H. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.00525 · Cited by 9

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Kim, D., Bae, J.-H., Jo, Y., & Choi, J. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1902.00829 · Cited by 23

A Method for Reducing the Forgetfulness of incremental Learning.

Shinozawa, K., & Shimohara, K. (1997) · International Conference on Neural Information Processing · Cited by 1

Mitigating catastrophic forgetting in incremental learning

Ahmad, M., & Karachi (2019) · doi:10.13140/rg.2.2.30582.34885 · Cited by 1

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Mittal, S., Galesso, S., & Brox, T. (2021) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw53098.2021.00390 · Cited by 113

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Dhar, P., Singh, R., Peng, K., Wu, Z., & Chellappa, R. (2019) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2019.00528 · Cited by 548