Results 61 to 70 of about 33,969 (261)

Universal adversarial perturbations for multiple classification tasks with quantum classifiers

Machine Learning: Science and Technology, 2023
Quantum adversarial machine learning is an emerging field that studies the vulnerability of quantum learning systems against adversarial perturbations and develops possible defense strategies.
Yun-Zhong Qiu
doaj   +1 more source

Quantum-inspired classification based on quantum state discrimination [PDF]

Quantum Machine Intelligence
19 pages, 4 ...
Emmanuel Zambrini Cruzeiro, Christine De Mol, Serge Massar, Stefano Pironio   +3 more
openaire   +3 more sources

Affinity‐Tuned Albumin Hitchhiking Extends the Bioorthogonal Capture Window in Pretargeting Radiotheranostics

Advanced Healthcare Materials, EarlyView.
Pharmacokinetic engineering of clickable radioligands was achieved via albumin hitchhiking approach within a pretargeted radiotheranostics delivery platform. This approach reduced rapid renal elimination, expanded bioorthogonal capture window, boosted tumor uptake by ∼3.5‐fold, and improved the tumor‐to‐liver ratio by ∼6‐fold.
Xie He, Nicholas L. Fletcher, Gayathri R. Ediriweera, Yifei Zhu, James Humphries, Christopher B. Howard, Jiazheng Wang, Craig A. Bell, Kristian Kempe, Kristofer J. Thurecht   +9 more
wiley   +1 more source

Quantum autoencoders for image classification

Quantum Machine Intelligence
Classical machine learning often struggles with complex, high-dimensional data. Quantum machine learning offers a potential solution, promising more efficient processing. The quantum convolutional neural network (QCNN), a hybrid algorithm, fits current noisy intermediate-scale quantum hardware.
Hinako Asaoka, Kazue Kudo
openaire   +2 more sources

Nanoplatforms for Sentinel and Tumor‐Draining Lymph Node Mapping: From Visualization to Pathway‐Informed Staging

Advanced Healthcare Materials, EarlyView.
Lymphotropic nanoplatforms integrate multimodal imaging with therapeutic guidance to map sentinel and tumor‐draining lymph nodes, revealing functional drainage, metastatic involvement, and nodal accessibility, while providing mechanistic insight to support precision surgical and therapeutic interventions.
Xu Chen, Nina Li, Meiyan Zou, Zihao Zhou, Rongwei Xu, Weiyao Feng, Xinyuan Zhao, Li Cui   +7 more
wiley   +1 more source

Peptide binding classification on quantum computers

Quantum Machine Intelligence
We conduct an extensive study on using near-term quantum computers for a task in the domain of computational biology. By constructing quantum models based on parameterised quantum circuits we perform sequence classification on a task relevant to the design of therapeutic proteins, and find competitive performance with classical baselines of similar ...
Charles London, Douglas Brown, Wenduan Xu, Sezen Vatansever, Christopher James Langmead, Dimitri Kartsaklis, Stephen Clark, Konstantinos Meichanetzidis   +7 more
openaire   +2 more sources

Ferroelectric Quantum Dots for Retinomorphic In‐Sensor Computing

Advanced Materials, EarlyView.
This work has provided a protocol for fabricating retinomorphic phototransistors by integrating ferroelectric ligands with quantum dots. The resulting device combines ferroelectricity, optical responsiveness, and low‐power operation to enable adaptive signal amplification and high recognition accuracy under low‐light conditions, while supporting ...
Tingyu Long, Huanyu Zhou, Jaewan Ko, Hongwei Tan, Jaemin Lim, Yanfei Zhao, Daehan Kang, Eojin Yoon, Gyeong‐Tak Go, Somin Kim, Seung‐Woo Lee, Chan‐Yul Park, Hyojun Choi, Hyeran Kim, Hyung Joong Yun, Sung Hyuk Park, Kwan Sik Park, Jeong Woo Park, Mungeun Kim, Yong Soo Cho, Ho Won Jang, Wenqiang Yang, Min Hyuk Park, Wan Ki Bae, Sebastiaan van Dijken, Joona Bang, Tae‐Woo Lee   +26 more
wiley   +1 more source

Bioinspired Adaptive Sensors: A Review on Current Developments in Theory and Application

Advanced Materials, EarlyView.
This review comprehensively summarizes the recent progress in the design and fabrication of sensory‐adaptation‐inspired devices and highlights their valuable applications in electronic skin, wearable electronics, and machine vision. The existing challenges and future directions are addressed in aspects such as device performance optimization ...
Guodong Gong, You Zhou, Qingxiu Li, Wenyu Zhao, Sunyingyue Geng, Hangfei Li, Yan‐Bing Leng, Shirui Zhu, Guanglong Ding, Yongbiao Zhai, Ziyu Lv, Ye Zhou, Su‐Ting Han   +12 more
wiley   +1 more source

Artificial Intelligence‐Assisted Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling

Advanced Materials, EarlyView.
AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll, Ivan Pinto‐Huguet, Enzo Rotunno, Thomas Galvani, Catalina Coll, Payam Habibzadeh Kavkani, Maria Chiara Spadaro, Yann‐Michel Niquet, Martin Børstad Eriksen, Sara Martí‐Sánchez, Georgios Katsaros, Giordano Scappucci, Peter Krogstrup, Giovanni Isella, Andreu Cabot, Gonzalo Merino, Pablo Ordejón, Stephan Roche, Vincenzo Grillo, Jordi Arbiol   +19 more
wiley   +1 more source

Causal Classification of Spatiotemporal Quantum Correlations

Physical Review Letters
29 ...
Minjeong Song, Varun Narasimhachar, Bartosz Regula, Thomas J. Elliott, Mile Gu   +4 more
openaire   +5 more sources