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Triple Memory Networks: a Brain-Inspired Method for Continual Learning

Triple Memory Networks: a Brain-Inspired Method for Continual Learning

IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2020
6 March 2020
Liyuan Wang
Bo Lei
Qian Li
Hang Su
Jun Zhu
Yi Zhong
    AAML
ArXiv (abs)PDFHTML

Papers citing "Triple Memory Networks: a Brain-Inspired Method for Continual Learning"

23 / 23 papers shown
HiCL: Hippocampal-Inspired Continual Learning
HiCL: Hippocampal-Inspired Continual Learning
Kushal Kapoor
Wyatt Mackey
Yiannis Aloimonos
Xiaomin Lin
CLL
250
0
0
19 Aug 2025
ESSENTIAL: Episodic and Semantic Memory Integration for Video Class-Incremental Learning
ESSENTIAL: Episodic and Semantic Memory Integration for Video Class-Incremental Learning
Jongseo Lee
Kyungho Bae
Kyle Min
Gyeong-Moon Park
J. Choi
CLLVLM
261
0
0
14 Aug 2025
Enhancing Pre-Trained Model-Based Class-Incremental Learning through Neural Collapse
Enhancing Pre-Trained Model-Based Class-Incremental Learning through Neural Collapse
Kun He
Zijian Song
Shuoxi Zhang
John E. Hopcroft
CLL
351
0
0
25 Apr 2025
Freeze and Cluster: A Simple Baseline for Rehearsal-Free Continual Category Discovery
Freeze and Cluster: A Simple Baseline for Rehearsal-Free Continual Category Discovery
Chuyu Zhang
Xueyang Yu
Peiyan Gu
Xuming He
CLL
454
0
0
12 Mar 2025
C-LoRA: Continual Low-Rank Adaptation for Pre-trained Models
C-LoRA: Continual Low-Rank Adaptation for Pre-trained Models
Xin Zhang
Liang Bai
Xian Yang
Jiye Liang
CLL
579
6
0
25 Feb 2025
Contrastive Federated Learning with Tabular Data Silos
Contrastive Federated Learning with Tabular Data Silos
Achmad Ginanjar
Xue Li
Wen Hua
Jiaming Pei
FedML
477
4
0
17 Feb 2025
ATLAS: Adapter-Based Multi-Modal Continual Learning with a Two-Stage
  Learning Strategy
ATLAS: Adapter-Based Multi-Modal Continual Learning with a Two-Stage Learning Strategy
Hong Li
Zhiquan Tan
Xingyu Li
Weiran Huang
CLLMoMe
241
7
0
14 Oct 2024
SLCA++: Unleash the Power of Sequential Fine-tuning for Continual
  Learning with Pre-training
SLCA++: Unleash the Power of Sequential Fine-tuning for Continual Learning with Pre-training
Gengwei Zhang
Liyuan Wang
Guoliang Kang
Ling Chen
Yunchao Wei
VLMCLL
287
10
0
15 Aug 2024
HiDe-PET: Continual Learning via Hierarchical Decomposition of Parameter-Efficient Tuning
HiDe-PET: Continual Learning via Hierarchical Decomposition of Parameter-Efficient Tuning
Liyuan Wang
Jingyi Xie
Xingxing Zhang
Hang Su
Jun Zhu
CLL
369
21
0
07 Jul 2024
Towards Incremental Learning in Large Language Models: A Critical Review
Towards Incremental Learning in Large Language Models: A Critical Review
M. Jovanovic
Peter Voss
ELMCLLKELM
760
11
0
28 Apr 2024
Brain-Inspired Continual Learning-Robust Feature Distillation and
  Re-Consolidation for Class Incremental Learning
Brain-Inspired Continual Learning-Robust Feature Distillation and Re-Consolidation for Class Incremental Learning
Hikmat Khan
N. Bouaynaya
Ghulam Rasool
CLL
314
1
0
22 Apr 2024
A Comprehensive Survey of Convolutions in Deep Learning: Applications,
  Challenges, and Future Trends
A Comprehensive Survey of Convolutions in Deep Learning: Applications, Challenges, and Future Trends
Abolfazl Younesi
Mohsen Ansari
Mohammadamin Fazli
A. Ejlali
Muhammad Shafique
Joerg Henkel
3DV
489
159
0
23 Feb 2024
Hessian Aware Low-Rank Perturbation for Order-Robust Continual Learning
Hessian Aware Low-Rank Perturbation for Order-Robust Continual LearningIEEE Transactions on Knowledge and Data Engineering (TKDE), 2023
Jiaqi Li
Yuanhao Lai
Rui Wang
Changjian Shui
Sabyasachi Sahoo
Charles Ling
Shichun Yang
Boyu Wang
Christian Gagné
Fan Zhou
CLL
424
3
0
26 Nov 2023
A Survey on Continual Semantic Segmentation: Theory, Challenge, Method
  and Application
A Survey on Continual Semantic Segmentation: Theory, Challenge, Method and ApplicationIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
Bo Yuan
Danpei Zhao
3DVCLL
422
39
0
22 Oct 2023
Incorporating Neuro-Inspired Adaptability for Continual Learning in
  Artificial Intelligence
Incorporating Neuro-Inspired Adaptability for Continual Learning in Artificial Intelligence
Liyuan Wang
Xingxing Zhang
Qian Li
Mingtian Zhang
Hang Su
Jun Zhu
Yi Zhong
346
94
0
29 Aug 2023
Complementary Learning Subnetworks for Parameter-Efficient
  Class-Incremental Learning
Complementary Learning Subnetworks for Parameter-Efficient Class-Incremental Learning
Depeng Li
Zhigang Zeng
CLL
304
1
0
21 Jun 2023
IF2Net: Innately Forgetting-Free Networks for Continual Learning
IF2Net: Innately Forgetting-Free Networks for Continual Learning
Depeng Li
Tianqi Wang
Bingrong Xu
Kenji Kawaguchi
Zhigang Zeng
Ponnuthurai Nagaratnam Suganthan
CLL
834
3
0
18 Jun 2023
SLCA: Slow Learner with Classifier Alignment for Continual Learning on a
  Pre-trained Model
SLCA: Slow Learner with Classifier Alignment for Continual Learning on a Pre-trained ModelIEEE International Conference on Computer Vision (ICCV), 2023
Gengwei Zhang
Liyuan Wang
Guoliang Kang
Ling-Hao Chen
Yunchao Wei
CLL
552
195
0
09 Mar 2023
A Comprehensive Survey of Continual Learning: Theory, Method and
  Application
A Comprehensive Survey of Continual Learning: Theory, Method and ApplicationIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
Liyuan Wang
Xingxing Zhang
Hang Su
Jun Zhu
KELMCLL
956
1,280
0
31 Jan 2023
Don't Stop Learning: Towards Continual Learning for the CLIP Model
Don't Stop Learning: Towards Continual Learning for the CLIP Model
Yuxuan Ding
Lingqiao Liu
Chunna Tian
Jingyuan Yang
Haoxuan Ding
CLLVLMKELM
250
78
0
19 Jul 2022
E2-AEN: End-to-End Incremental Learning with Adaptively Expandable
  Network
E2-AEN: End-to-End Incremental Learning with Adaptively Expandable Network
Guimei Cao
Zhanzhan Cheng
Yunlu Xu
Duo Li
Shiliang Pu
Yi Niu
Leilei Gan
CLL
270
2
0
14 Jul 2022
AFEC: Active Forgetting of Negative Transfer in Continual Learning
AFEC: Active Forgetting of Negative Transfer in Continual LearningNeural Information Processing Systems (NeurIPS), 2021
John Giorgi
Mingtian Zhang
Zhongfan Jia
Qian Li
Chenglong Bao
Kaisheng Ma
Jun Zhu
Yi Zhong
CLL
235
117
0
23 Oct 2021
Always Be Dreaming: A New Approach for Data-Free Class-Incremental
  Learning
Always Be Dreaming: A New Approach for Data-Free Class-Incremental LearningIEEE International Conference on Computer Vision (ICCV), 2021
James Smith
Yen-Chang Hsu
John C. Balloch
Yilin Shen
Hongxia Jin
Z. Kira
CLL
446
208
0
17 Jun 2021
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