Results 91 to 100 of about 21,160 (284)

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

Advanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan, Tian Zhang, Jiawei Dong, Yubao Xie, Kaifeng Zhong, Wei Guan, Haiqiao Wei, Changcheng Fu, Yaqiong Su   +8 more
wiley   +1 more source

Applications of Some Deep Learning Algorithms to Predict Trend in the Forex Exchange Market [PDF]

Mathematics and Modeling in Finance
Predicting time series has always been one of the challenges in the financial markets. With the increase in the amount of data, the need to use modern tools instead of classical statistical and time series methods has become clear.
Mohammad Ali Jafari, Sina Ghasemilo
doaj   +1 more source

Universal Equivariant Multilayer Perceptrons

CoRR, 2020
Group invariant and equivariant Multilayer Perceptrons (MLP), also known as Equivariant Networks, have achieved remarkable success in learning on a variety of data structures, such as sequences, images, sets, and graphs. Using tools from group theory, this paper proves the universality of a broad class of equivariant MLPs with a single hidden layer. In
openaire   +3 more sources

Ambipolar Organic–Inorganic Heterostructure Transistor Array for Integrated Visual Information Processing

Advanced Science, EarlyView.
We present an organic–inorganic heterostructure transistor array for neuromorphic computing, achieving 95.6% MNIST accuracy and 1.2 fJ per operation, with dynamic spatiotemporal encoding and precise vehicle direction detection under combined optical and electrical stimulation.
Wen‐Min Zhong, Wenbin Zhang, Yu‐Xiang Zeng, JiYu Zhao, Ziqi Jia, Loganathan Veeramuthu, Guanglong Ding, Yan Yan, Meng Zhang, Su‐Ting Han, Vellaisamy A. L. Roy, Fengyun Wang, Chi‐Ching Kuo, Ye Zhou   +13 more
wiley   +1 more source

A Crack‐Based One‐Dimensional Microspheres Array Enables Thermal–Mechanical Decoupled Dual‐Functional Sensing

Advanced Science, EarlyView.
Inspired by Nostoc, a crack‐based one‐dimensional microspheres array (COMA) sensor is developed, which stabilizes crack geometry under isotropic expansion, enabling a predictable, monotonic thermal response from which true strain can be accurately extracted. The COMA sensor exhibits high sensitivity at ultralow deformation (gauge factor up to 89) and a
Wanqing Xu, Hongyi Tu, Zehao Wang, Tianyu Zhu, Chao Wang, Min Chen, Lan Shi, Limin Wu   +7 more
wiley   +1 more source

Decoding Spatial Heterogeneity and Multi‐Omics Regulation with Hierarchical Graph Learning

Advanced Science, EarlyView.
ABSTRACT Recent advances in spatial multi‐omics technologies have enabled the simultaneous profiling of multiple molecular layers within the same tissue slice, providing unprecedented opportunities to investigate tissue spatial organization. However, most existing computational methods identify spatial domains in a purely data‐driven manner, rarely ...
Jiazhou Chen, Jiahui Xie, Yi Liao, Junyu Li, Longqi Liu, Xin Gao, Hongmin Cai   +6 more
wiley   +1 more source

STAID: A Self‐Refining Deep Learning Framework for Spatial Cell‐Type Deconvolution with Biologically Informed Modeling

Advanced Science, EarlyView.
STAID is a unified deep learning framework that couples iterative pseudo‐spot refinement with neural network training through a feedback loop and exploits gene co‐expression information to model higher‐order interactions, achieving accurate and robust cell‐type deconvolution in spatial transcriptomics.
Jixin Liu, Shuli Sun, Zhengliang Lv, Xinyu Liu, Yihua Wang, Bingqiang Liu   +5 more
wiley   +1 more source

Image super‐resolution reconstruction based on implicit image functions

IET Image Processing
Image super‐resolution (SR) reconstruction is a key technique for improving image quality and details. Conventional methods are frequently limited by interpolation, filtering, or statistical approaches; thus, they are unable to reconstruct high‐quality ...
Hai Lin, JunJie Yang
doaj   +1 more source

Diffusion‐Based Generative Model With Scaffold‐Hopping Strategy Yields Highly Potent Bioactive Molecules

Advanced Science, EarlyView.
SMarT‐Diff introduces a multi‐objective generative paradigm that integrates scaffold hopping with structure‐aware scoring to enable controlled exploration beyond the training distribution. The framework consistently balances drug‐likeness, synthesizes accessibility and bioactivity, yielding chemically diverse candidates with enhanced properties.
Yuwei Yang, Xiaoqing Gong, Shukai Gu, Jing Li, Bo Liu, Yanan Tian, Qianqian Zhang, Xiaojun Yao, Huanxiang Liu   +8 more
wiley   +1 more source

Learning neural implicit surfaces with local probability standard variance

IET Image Processing
Reconstructing geometric shapes from sparse multiview has always been a challenging task. With the development of neural implicit surfaces, geometry‐based volume rendering surface reconstruction methods have been proven to be able to reconstruct high ...
Hai Nan, Kai Zhao, Xuefei Han, Dongjie Zhao   +3 more
doaj   +1 more source