Results 91 to 100 of about 23,653 (255)

PegasosQSVM: A Quantum Machine Learning Approach for Accurate Fake News Detection

Applied Artificial Intelligence
The rapid spread of fake news on social media poses a significant threat to modern societies. Traditional machine learning approaches have limitations in handling the ever-increasing volume and complexity of data.
Mehdi Khalil, Chi Zhang, Zhiwei Ye, Peng Zhang   +3 more
doaj   +1 more source

Quantum machine learning [PDF]

National Science Review, 2018
Allcock, Jonathan, Zhang, Shengyu
openaire   +2 more sources

Space‐Time Coding Conformal Metasurfaces for Multifrequency Beam Steering and Shaping

Advanced Materials, EarlyView.
Space‐time coding conformal metasurfaces enable dynamic wave control on curved surfaces by combining programmable spatial patterns with temporal modulation. This study shows that a single conformal aperture can independently manipulate multiple frequency components, achieving multifunctional beam shaping and steering, with implications for ...
Filippo Pepe, Lei Zhang, Yi Ning Zheng, Xiao Qing Chen, Ivan Iudice, Giuseppe Castaldi, Marco Di Renzo, Tie Jun Cui, Vincenzo Galdi   +8 more
wiley   +1 more source

Machine learning by unitary tensor network of hierarchical tree structure

New Journal of Physics, 2019
The resemblance between the methods used in quantum-many body physics and in machine learning has drawn considerable attention. In particular, tensor networks (TNs) and deep learning architectures bear striking similarities to the extent that TNs can be ...
Ding Liu, Shi-Ju Ran, Peter Wittek, Cheng Peng, Raul Blázquez García, Gang Su, Maciej Lewenstein   +6 more
doaj   +1 more source

From Behavior to Dynamics: Decoding Carrier Roles in Cu‐based Photocathodes for Solar‐Driven CO2 Reduction

Advanced Materials, EarlyView.
The performance of Cu‐based photocathodes in photoelectrochemical CO2 reduction is not governed by catalytic sites alone, but by the dynamic journey of photogenerated carriers. This review decodes how carrier generation, recombination, transport, accumulation, extraction, and electrolyte coupling shape catalytic activity, selectivity, and stability ...
Yi‐Cheng Wang, Chenyu Xu, Peng‐Fei Sui, Yi Liu, Xiaolei Wang, Jing‐Li Luo   +5 more
wiley   +1 more source

Optoelectronic Nanofluidic Neural Networks for Ionic Computing

Advanced Materials, EarlyView.
An ion‐based optoelectronic nanofluidic memristor enables neuromorphic computing in aqueous environments. With tunable ionic memory and multimodal synaptic plasticity, it realizes densely connected ionic neural networks capable of image classification, motion prediction, logic computation, and real‐time in‐sensor computing, advancing fully connected ...
Yaxin Huang, Zhiyuan Du, Changjin Wu, Binglin Zeng, Yingnan Cao, Mingliang Li, Liren Zhang, Qingxin Guo, Chao Huang, Can Li, Jinyao Tang   +10 more
wiley   +1 more source

Toward structure-preserving quantum encodings

Physical Review Research
Harnessing the potential computational advantage of quantum computers for machine learning tasks relies on the uploading of classical data onto quantum computers through what are commonly referred to as quantum encodings. The choice of such encodings may
Arthur J. Parzygnat, Tai-Danae Bradley, Andrew Vlasic, Anh Pham   +3 more
doaj   +1 more source

From the Discovery of the Giant Magnetocaloric Effect to the Development of High‐Power‐Density Systems

Advanced Materials Technologies, EarlyView.
The article overviews past and current efforts on caloric materials and systems, highlighting the contributions of Ames National Laboratory to the field. Solid‐state caloric heat pumping is an innovative method that can be implemented in a wide range of cooling and heating applications.
Agata Czernuszewicz, Yaroslav Mudryk, Jun Cui, Lucas Griffith, Duane D. Johnson, Julie Slaughter   +5 more
wiley   +1 more source

Quantum machine learning and quantum biomimetics: A perspective

Machine Learning: Science and Technology, 2020
AbstractQuantum machine learning has emerged as an exciting and promising paradigm inside quantum technologies. It may permit, on the one hand, to carry out more efficient machine learning calculations by means of quantum devices, while, on the other hand, to employ machine learning techniques to better control quantum systems.
openaire   +4 more sources

Benchmarking Coaxial and Angular Optical Emission Spectroscopy With Recommendations for Reliable Compositional In Situ Monitoring During Laser Powder Bed Fusion

Advanced Materials Technologies, EarlyView.
ABSTRACT Real‐time insight into local chemistry is critical for reliable part quality in additive manufacturing, especially laser powder bed fusion (PBF‑LB/M), where rapid thermal cycles and localized evaporation can undermine part performance. Optical emission spectroscopy (OES) offers non‑intrusive, in situ plume monitoring, but detection geometry ...
Philipp Gabriel, Bastian Jülich, Anna Rosa Ziefuss, Florian Eibl, Stephan Barcikowski   +4 more
wiley   +1 more source