Results 121 to 130 of about 21,815 (240)

Quantum state tomography using quantum machine learning

Quantum Machine Intelligence
18 pages, 19 ...
Nouhaila Innan, Owais Ishtiaq Siddiqui, Shivang Arora, Tamojit Ghosh, Yasemin Poyraz Koçak, Dominic Paragas, Abdullah Al Omar Galib, Muhammad Al-Zafar Khan, Mohamed Bennai   +8 more
openaire   +2 more sources

Solid Harmonic Wavelet Bispectrum for Image Analysis

Advanced Science, EarlyView.
The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown, Mathilda Avirett‐Mackenzie, Carolin Villforth, Georgios Exarchakis   +3 more
wiley   +1 more source

Recent Advances and Perspectives on Field‐Effect Transistors for Artificial Visual Neuromorphic Systems

Advanced Science, EarlyView.
This review presents a comprehensive overview of FET‐based visual neuromorphic systems, covering their semiconductor materials, core device architectures, and operating mechanisms. It further reviews their implementation in emulating biological visual functions, addresses current technological challenges, and outlines future development directions. The
Liu Yaqian, Lang Menghua, Xu Yihang, Zhang Manyu, Lei Chunkang, Lu Xiaozhou, Dou Yi, Wang Lingli, Jiang Liying, Hu Yuanyuan, Chen Huipeng, Jiang Lang   +11 more
wiley   +1 more source

Encoding Cumulation to Learn Perturbative Nonlinear Oscillatory Dynamics

Advanced Science, EarlyView.
Weak nonlinearities critically shape the long term behavior of oscillatory systems but are difficult to identify from data. A data‐driven framework is introduced to infer governing equations of weakly nonlinear oscillators from sparse and noisy observations.
Teng Ma, Ting‐Ting Gao, Wei Cui, Attilio Frangi, Gang Yan, Lin Zhao   +5 more
wiley   +1 more source

Integrating Spatial Proteogenomics in Cancer Research

Advanced Science, EarlyView.
Xx xx. ABSTRACT Background: Spatial proteogenomics marks a paradigm shift in oncology by integrating molecular analysis with spatial information from both spatial proteomics and other data modalities (e.g., spatial transcriptomics), thereby unveiling tumor heterogeneity and dynamic changes in the microenvironment.
Yida Wang, Yang Wu, Feng Zhang, Parthiban Periasamy, Haiyue You, Denise Goh, Rachel Elizabeth Ann Fincham, Xin Ning, Danping Wu, Lu Liu, Ying Jiang, Zhiwen Qian, Joe Yeong, Yan Zhang   +13 more
wiley   +1 more source

Why Computational Photochemistry Is Challenging and Will Probably Remain So: A Quantum Chemist's Perspective

Advanced Science, EarlyView.
Computational Photochemistry has made great strides in recent decades, but the investigation of larger molecules remains a challenge due to the inherent dilemma between the increasing computational accuracy required as the molecule size increases and the inevitable explosion in computational effort.
Andreas Dreuw
wiley   +1 more source

GBS-Assisted Quantum Unsupervised Machine Learning on a Universal Programmable Integrated Quantum Chip

Research
Quantum machine learning stands poised as a forefront application for near-term quantum devices, addressing scalability challenges posed by classical computers in handling large datasets.
Huihui Zhu, Wei Luo, Rudai Yan, Chao Ren, Jia Guo, Zichao Zhao, Haoran Ma, Tian Chen, Feng Gao, Leong Chuan Kwek, Hong Cai, Yuehai Wang, Jianyi Yang, Ai-Qun Liu   +13 more
doaj   +1 more source

Implementation and empirical evaluation of a quantum machine learning pipeline for local classification. [PDF]

PLoS One, 2023
Zardini E, Blanzieri E, Pastorello D.
europepmc   +1 more source

Digital‐Analog Quantum Machine Learning

Advanced Intelligent Discovery
Machine learning algorithms are extensively used in an increasing number of systems, applications, technologies, and products, both in industry and in society as a whole. They enable computing devices to learn from previous experience and therefore improve their performance in a certain context or environment.
openaire   +3 more sources

Blind Quantum Machine Learning with Quantum Bipartite Correlator

Physical Review Letters
Distributed quantum computing is a promising computational paradigm for performing computations that are beyond the reach of individual quantum devices. Privacy in distributed quantum computing is critical for maintaining confidentiality and protecting the data in the presence of untrusted computing nodes. In this work, we introduce novel blind quantum
Changhao Li, Boning Li, Omar Amer, Ruslan Shaydulin, Shouvanik Chakrabarti, Guoqing Wang, Haowei Xu, Hao Tang, Isidor Schoch, Niraj Kumar, Charles Lim, Ju Li, Paola Cappellaro, Marco Pistoia   +13 more
openaire   +3 more sources