Results 41 to 50 of about 3,187 (246)

Resource Efficient Boolean Function Solver on Quantum Computer [PDF]

Quantum
Nonlinear boolean equation systems play an important role in a wide range of applications. Grover's algorithm is one of the best-known quantum search algorithms in solving the nonlinear boolean equation system on quantum computers.
Xiang Li, Hanxiang Shen, Weiguo Gao, Yingzhou Li   +3 more
doaj   +1 more source

Sparse representation based intraframe and semi‐intraframe video coding schemes for low bitrates

IET Image Processing, 2021
This paper proposes some extensions of the successful sparse coding of still images to intraframe and semi‐intraframe video coding. The presented frameworks apply the efficient K‐singular value decomposition and recursive least squares dictionary ...
Maziar Irannejad, Homayoun Mahdavi‐Nasab   +1 more
doaj   +1 more source

Compressed SUSY searches with the Recursive Jigsaw Reconstruction [PDF]

Proceedings of The European Physical Society Conference on High Energy Physics — PoS(EPS-HEP2017), 2017
The Recursive Jigsaw Reconstruction technique provides a powerful way to search for new physics in scenarios with multiple missing particles in the final state. By defining a specific input decay tree we demonstrate a new approach to search for supersymmetry in scenarios where the mass difference between the parent super-particles and the lightest ...
openaire   +1 more source

Neural Information Processing and Time‐Series Prediction with Only Two Dynamical Memristors

Advanced Electronic Materials, EarlyView.
The present study demonstrates how simple circuits with only two memristive devices are utilized to perform high complexity temporal information processing tasks, like neural spike detection in noisy environment, or time‐series prediction. This circuit simplicity is enabled by the dynamical complexity of the memristive devices, i.e.
Dániel Molnár, Tímea Nóra Török, János Volk, Roland Kövecs, László Pósa, Péter Balázs, György Molnár, Nadia Jimenez Olalla, Zoltán Balogh, János Volk, Juerg Leuthold, Miklós Csontos, András Halbritter   +12 more
wiley   +1 more source

Feature Selection for Machine Learning‐Driven Accelerated Discovery and Optimization in Emerging Photovoltaics: A Review

Advanced Intelligent Discovery, EarlyView.
Feature selection combined with machine learning and high‐throughput experimentation enables efficient handling of high‐dimensional datasets in emerging photovoltaics. This approach accelerates material discovery, improves process optimization, and strengthens stability prediction, while overcoming challenges in data quality and model scalability to ...
Jiyun Zhang, Jiayi Tan, Qizhen Song, Tian Du, Jens Hauch, Christoph J. Brabec   +5 more
wiley   +1 more source

Compressed Sensing Image Reconstruction Via Recursive Spatially Adaptive Filtering [PDF]

2007 IEEE International Conference on Image Processing, 2007
We introduce a new approach to image reconstruction from highly incomplete data. The available data are assumed to be a small collection of spectral coefficients of an arbitrary linear transform. This reconstruction problem is the subject of intensive study in the recent field of "compressed sensing" (also known as "compressive sampling"). Our approach
Karen Egiazarian, Alessandro Foi, Vladimir Katkovnik   +2 more
openaire   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

Roadmap on Artificial Intelligence‐Augmented Additive Manufacturing

Advanced Intelligent Systems, EarlyView.
This Roadmap outlines the transformative role of artificial intelligence‐augmented additive manufacturing, highlighting advances in design, monitoring, and product development. By integrating tools such as generative design, computer vision, digital twins, and closed‐loop control, it presents pathways toward smart, scalable, and autonomous additive ...
Ali Zolfagharian, Liuchao Jin, Qi Ge, Wei‐Hsin Liao, Andrés Díaz Lantada, Francisco Franco Martínez, Tianyu Zhang, Tao Liu, Charlie C. L. Wang, Mohammad Hossein Mosallanejad, Reza Ghanavati, Abdollah Saboori, Alejandro De Blas De Miguel, William Solórzano‐Requejo, Yi Cai, Xiangyang Dong, Huangyi Qu, Najmeh Samadiani, Guangyan Huang, Austin Downey, Yanzhou Fu, Lang Yuan, Tsz‐Kwan (Glory) Lee, Arbind Agrahari Baniya, Eisha Waseem, Abdul Rahman Sani, Abbas Z. Kouzani, Yijia Wu, Markus P. Nemitz, Masoud Shirzad, Dageon Oh, Seung Yun Nam, Amedeo Franco Bonatti, Irene Chiesa, Gabriele Maria Fortunato, Giovanni Vozzi, Carmelo De Maria, Mahdi Bodaghi   +37 more
wiley   +1 more source