Results 91 to 100 of about 6,336,923 (296)

Organic Electrochemical Transistors for Neuromorphic Bioelectronics: Materials and Manufacturing Technologies

Advanced Science, EarlyView.
Organic electrochemical transistors bridge biological ionic signaling and neuromorphic computation through volumetric electrochemical gating. This review connects Organic mixed ionic–electronic conductor materials, device architectures, and manufacturing technologies to show how geometry, ion transport, and fabrication strategies program plasticity ...
Hyunjin Lee, Jihyang Park, Xinyi Wang, Yueqi Deng, Jiashu Ren, Tao Zhou   +5 more
wiley   +1 more source

Structure-aware federated hypergraph continual learning

Journal of King Saud University: Computer and Information Sciences
Federated hypergraph continual learning requires decentralized clients to learn a sequence of tasks over high-order relational data without directly sharing raw local data. This setting is challenging because hypergraph neural networks rely on hyperedges
Yanxin Hu, Xiaoman Liu, Zhenzhen Xie, Junjie Pang, Chao Cheng   +4 more
doaj   +1 more source

Continual Learning With Quasi-Newton Methods

IEEE Access
Catastrophic forgetting remains a major challenge when neural networks learn tasks sequentially. Elastic Weight Consolidation (EWC) attempts to address this problem by introducing a Bayesian-inspired regularization loss to preserve knowledge of ...
Steven Vander Eeckt, Hugo Van Hamme
doaj   +1 more source

Multi-task Learning Approach to Stability-Plasticity Balance in Continual Learning [PDF]

Jisuanji kexue yu tansuo
Continual learning (CL) is an advanced paradigm in machine learning designed to simulate and optimize human learning mechanisms. It enables machines to incrementally acquire new knowledge, update prior knowledge, and effectively accumulate and utilize ...
ZHANG Mimi, FENG Xiang, YU Huiqun
doaj   +1 more source

Mathematics of Continual Learning

CoRR
Continual learning is an emerging subject in machine learning that aims to solve multiple tasks presented sequentially to the learner without forgetting previously learned tasks. Recently, many deep learning based approaches have been proposed for continual learning, however the mathematical foundations behind existing continual learning methods remain
Liangzu Peng, René Vidal
openaire   +3 more sources

Beyond Conventional: A Review of Phytochemical‐Hydrogel Systems Enhanced by AI and 3D Printing for Chronic Wound Management

Advanced Science, EarlyView.
This review systematically bridges chronic wound pathology with natural phytochemical hydrogel therapeutics. A pathology‐to‐phytochemical mechanistic mapping framework is established, linking specific wound hallmarks to targeted phytochemical interventions.
Yitao Zhou, Xing Liu, Cuiyi Wang, Xiaoxuan Zhao, Pengrun Zhang, Jingjing Gu, Qiuhua Sun, Malcolm Xing, Yeqin Yang   +8 more
wiley   +1 more source

Modular-Relatedness for Continual Learning

, 2022
We realized one conclusion in the submission is erroneous and disconnected from the results shown in one theorem is.
Ammar Shaker, Francesco Alesiani, Shujian Yu   +2 more
openaire   +4 more sources

Continual Multi-agent Reinforcement Learning applied in cooperative games [PDF]

openReinforcement Learning combined with Continual Learning offers the poten- tiality to explore many of the challenges of the modern era in almost every field of the society, from financial and portfolio management to human-robot coop- eration in the ...
CASADEI, OLIVIA
core  

Attention Distraction: Watermark Removal Through Continual Learning with Selective Forgetting

, 2022
Fine-tuning attacks are effective in removing the embedded watermarks in deep learning models. However, when the source data is unavailable, it is challenging to just erase the watermark without jeopardizing the model performance.
Gao, L, Xiang, Y, Zhang, LY, Zhong, Q, Hu, S, Zhang, J   +5 more
core   +1 more source

Closing the Loop: High‐Precision 3D Photofabrication in Living Tissues

Advanced Science, EarlyView.
Writing 3D microstructures inside living tissue demands more than laser access; It demands information. Hierarchical sensing captures thermal and mechanical states across pulse‐train, voxel, and structure timescales, feeding a controller that steers the laser in real time.
Amirbahador Zeynali, Mangirdas Malinauskas, Giuseppe Chirico   +2 more
wiley   +1 more source