Results 131 to 140 of about 1,029,862 (299)

Achieving High ON State Current through Ferroelectric Polarization‐Dependent Interfacial Resistance Switching in Undoped Orthorhombic HfO2 Films

Advanced Functional Materials, EarlyView.
Ferroelectric tunnel junction devices based on epitaxial undoped ferroelectric HfO2 films demonstrate stable switching endurance of over 106 switching cycles, low write voltages of ±3 V, 16 measured resistance states, and neuromorphic capability.
Markus Hellenbrand, Nuno Estrócio, Ji S. Kim, Babak Bakhit, Marian C. Istrate, Corneliu Ghica, Tiago Rebelo, Nives Strkalj, Abin Varghese, Bernardo Almeida, Luís S. Marques, Bipin Rajendran, Judith L. MacManus‐Driscoll, José P. B. Silva   +13 more
wiley   +1 more source

Twin Contrastive Learning for Multi-View Clustering

IEEE Access
Multi-view Clustering (MVC) utilizes the complementary and consistent information between multiple views or modal data to more comprehensively reveal the inherent structure and patterns of data. However, mining the invariance and complementarity of multi-
Ansi Zhang, Yang Zheng, Xiaohua Wang, Jie Hu   +3 more
doaj   +1 more source

scPML: pathway-based multi-view learning for cell type annotation from single-cell RNA-seq data. [PDF]

Commun Biol, 2023
Du ZH, Hu WL, Li JQ, Shang X, You ZH, Chen ZZ, Huang YA.   +6 more
europepmc   +1 more source

Solution‐Processed Two‐Dimensional Indium Oxide on Sodium‐Embedded Alumina for Reconfigurable Optoelectronic Synaptic Transistors

Advanced Functional Materials, EarlyView.
Wafer‐scale two‐dimensioanl In2Se3 oxidized into InOx on sodium‐embedded beta‐alumina enables multifunctional reconfigurable electronics. Sodium ions accumulate within distinct spatial distribution under drain‐controlle and gate‐controlled operation. Drain‐control operation gives controllability of ultraviolet‐driven optoelectronic synaptic conductance
Jinhong Min, Yonghyun Albert Kwon, Hyunbin Kim, Jihyun Kim, Myeongjin Jung, Jaewon Heo, Gwang Ya Kim, Vlastimil Mazanek, Zdeněk Sofer, In Soo Kim, Jeong Ho Cho, Hyesung Park, Sang Min Won, Joohoon Kang   +13 more
wiley   +1 more source

Incomplete multi-view partial multi-label classification via deep semantic structure preservation

Complex & Intelligent Systems
Recent advances in multi-view multi-label learning are often hampered by the prevalent challenges of incomplete views and missing labels, common in real-world data due to uncertainties in data collection and manual annotation.
Chaoran Li, Xiyin Wu, Pai Peng, Zhuhong Zhang, Xiaohuan Lu   +4 more
doaj   +1 more source

Machine Learning‐Assisted Inverse Design of Soft and Multifunctional Hybrid Liquid Metal Composites

Advanced Functional Materials, EarlyView.
A machine learning framework is presented for inverse design of synthesizable multifunctional composites containing both liquid metal and solid inclusions. By integrating physics‐based modeling, data‐driven prediction, and Bayesian optimization, the approach enables intelligent design of experiments to identify optimal compositions and realize these ...
Lijun Zhou, Yunsik Ohm, Ren‐Mian Chin, Olivia Kerr, Krithika Manohar, Mohammad H. Malakooti   +5 more
wiley   +1 more source

Semi-Supervised Multi-View Ensemble Learning Based On Extracting Cross-View Correlation

Advances in Electrical and Computer Engineering, 2016
Correlated information between different views incorporate useful for learning in multi view data. Canonical correlation analysis (CCA) plays important role to extract these information.
ZALL, R., KEYVANPOUR, M. R.
doaj   +1 more source

Self-paced Multi-view Learning for CT-based severity assessment of COVID-19. [PDF]

Biomed Signal Process Control, 2023
Liu Y, Chen B, Zhang Z, Yu H, Ru S, Chen X, Lu G.   +6 more
europepmc   +1 more source

Robust Lifelong Multi-task Multi-view Representation Learning [PDF]

, 2018
The state-of-the-art multi-task multi-view learning (MTMV) tackles the learning scenario where multiple tasks are associated with each other via multiple shared feature views.
Li, Jun, Fu Y(付昀), Sun G(孙干), Cong Y(丛杨)   +3 more
core  

Integrated Field‐Free SOT Domain‐Wall Synapses and MTJ Stochastic Neurons for Hardware Boltzmann Machines

Advanced Functional Materials, EarlyView.
Field‐free spin‐orbit torque domain‐wall synapses integrated with stochastic MTJ neurons enable compact hardware Boltzmann machines. Leveraging intrinsic stochasticity and multi‐level conductance, the system achieves efficient probabilistic learning with high accuracy, demonstrating a scalable spintronic platform for energy‐efficient edge AI.
Aijaz H. Lone, Meng Tang, Camelia Florica, Bin He, Jingkai Xu, Selma Amara, Georgian Melinte, Xixiang Zhang, Gianluca Setti   +8 more
wiley   +1 more source