Results 61 to 70 of about 1,077,071 (292)

TuckerDNCaching: high-quality negative sampling with tucker decomposition

Journal of Intelligence and Information Systems, 2023
Knowledge Graph Embedding (KGE) translates entities and relations of knowledge graphs (KGs) into a low-dimensional vector space, enabling an efficient way of predicting missing facts. Generally, KGE models are trained with positive and negative examples,
Tiroshan Madushanka, R. Ichise
semanticscholar   +1 more source

Novel Functional Materials via 3D Printing by Vat Photopolymerization

Advanced Functional Materials, EarlyView.
This Perspective systematically analyzes strategies for incorporating functionalities into 3D‐printed materials via Vat Photopolymerization (VP). It explores the spectrum of achievable functionalities in recently reported novel materials—such as conductive, energy‐storing, biodegradable, stimuli‐responsive, self‐healing, shape‐memory, biomaterials, and
Sergey S. Nechausov, Patrick Fesser, Boris A. Bulgakov, Ulrich S. Schubert   +3 more
wiley   +1 more source

Hybrid Low-Rank Tensor CP and Tucker Decomposition with Total Variation Regularization for HSI Noise Removal

Wireless Communications and Mobile Computing, 2023
The acquired hyperspectral images (HSIs) are affected by a mixture of several types of noise, which often suffer from information missing. Corrupted HSIs limit the precision of the subsequent processing.
Luo Xuegang, Lv Junrui, Wang Bo, Wang Juan   +3 more
semanticscholar   +1 more source

Metal–Organic Frameworks for Gaseous Pollutant Management: From Capture to Neutralization and Reutilization

Advanced Functional Materials, EarlyView.
This review maps how MOFs can manage hazardous gases by combining adsorption, neutralization, and reutilization, enabling sustainable air‐pollution control. Covering chemical warfare agent simulants, SO2, NOx, NH3, H2S, and volatile organic compounds, it highlights structure‐guided strategies that boost selectivity, water tolerance, and cycling ...
Yuanmeng Tian, Zeyu Tao, Kaikai Ma, Xiaoliang Wang, Bo Yu, Yiu Wan Yip, Zhijie Chen, Jin Shang, Bin Fei   +8 more
wiley   +1 more source

A tensor compression algorithm using Tucker decomposition and dictionary dimensionality reduction

International Journal of Distributed Sensor Networks, 2020
Tensor compression algorithms play an important role in the processing of multidimensional signals. In previous work, tensor data structures are usually destroyed by vectorization operations, resulting in information loss and new noise. To this end, this
Chenquan Gan, Junwei Mao, Zufan Zhang, Qingyi Zhu   +3 more
doaj   +1 more source

Harmonic Retrieval with $L_1$-Tucker Tensor Decomposition

, 2021
Harmonic retrieval (HR) has a wide range of applications in the scenes where signals are modelled as a summation of sinusoids. Past works have developed a number of approaches to recover the original signals. Most of them rely on classical singular value decomposition, which are vulnerable to unexpected outliers.
Luan, Zhenting, Ming, Zhenyu, Wu, Yuchi, Han, Wei, Chen, Xiang, Bai, Bo, Zhang, Liping   +6 more
openaire   +2 more sources

Rapid Fabrication of Self‐Propelled and Steerable Magnetic Microcatheters for Precision Medicine

Advanced Materials, EarlyView.
A rapid Joule heating fabrication method for the production of self‐propelling, adaptive microcatheters, with tunable stiffness and integrated microfluidic channels is presented. Demonstrated through three microrobotic designs, including a steerable guiding catheter, an untethered wave‐crawling TubeBot, and a distal‐end propelled microcatheter, it was ...
Zhi Chen, Boris Rivkin, David Castellanos‐Robles, Ivan Soldatov, Lukas Beyer, Mariana Medina‐Sánchez   +5 more
wiley   +1 more source

Hypergraph regularized nonnegative triple decomposition for multiway data analysis

Scientific Reports
Tucker decomposition is widely used for image representation, data reconstruction, and machine learning tasks, but the calculation cost for updating the Tucker core is high.
Qingshui Liao, Qilong Liu, Fatimah Abdul Razak   +2 more
doaj   +1 more source

BATUDE: Budget-Aware Neural Network Compression Based on Tucker Decomposition

AAAI Conference on Artificial Intelligence, 2022
Model compression is very important for the efficient deployment of deep neural network (DNN) models on resource-constrained devices. Among various model compression approaches, high-order tensor decomposition is particularly attractive and useful ...
Miao Yin, Huy Phan, Xiao Zang, Siyu Liao, Bo Yuan   +4 more
semanticscholar   +1 more source

Porous Iridium Oxide Inverse Opal Catalysts Enable Efficient PEM Water Electrolysis

Advanced Materials, EarlyView.
Porous iridium‐based inverse opal (IrOx‐IO) structures are introduced as high‐performance, unsupported PEM‐WE anode catalysts. Their electrochemical behavior is analyzed through porosity/surface area tuning, voltage breakdown, and circuit modeling.
Sebastian Möhle, Kerolus Nasser Nagi Nasralla, Jakub Drnec, William Chèvremont, Peter Strasser   +4 more
wiley   +1 more source