Results 241 to 250 of about 1,052,376 (334)

Application of Normalizing Flows in Deep Reinforcement Learning

openNormalizing Flow (NF) models have recently emerged as a powerful class of generative models capable of learning expressive probability distributions through invertible transformations.
BOSCOLO MENEGUOLO, FRANCESCO
core  

3D Large‐Scale Subwavelength‐Resolution Sound Sheet Tomography Based on an Active and Programmable Circular Meta‐Array

Advanced Science, EarlyView.
A programmable 2048‐element circular ultrasound array combined with a compact acoustic lens produces a thin “sound sheet” over a large field of view, and records echoes with wide angular diversity across the ring aperture. Coherence‐enhanced beamforming converts full‐matrix data into high‐contrast tomographic slices, delivering near‐diffraction‐limited
Qiu‐De Zhang, Zi‐Bin Lin, Zhuo Chen, Zhao‐Hui Liu, Jin‐Lian He, Jun‐Jie Song, Long‐Sheng Zeng, Liang Zhou, Ming‐Yue Ding, Yu‐Gui Peng, Ming Yuchi, Xue‐Feng Zhu   +11 more
wiley   +1 more source

Correction to: Deep reinforcement learning for automatic anatomic CT landmark localization in Stanford Type B aortic dissection. [PDF]

Radiol Adv
europepmc   +1 more source

Visualising backward information propagation in deep reinforcement learning from a variational data assimilation perspective. [PDF]

Sci Rep
Wang KY.
europepmc   +1 more source

Full‐Body AI Agent: A Perspective on Multi‐Scale Collaborative AI for Systemic Biology and Precision Medicine

Advanced Science, EarlyView.
We propose the Full‐Body AI Agent, a multi‐scale collaborative framework with 7 biological‐layer agents. It unifies multi‐omics/clinical data via standardized protocols, enabling phenotype‐guided closed‐loop reasoning, quantitative evaluation, and LLM safeguards, with promising applications in tumor metastasis modeling and precision drug development ...
Aoqi Wang, Jiajia Liu, Jianguo Wen, Yangyang Luo, Zhiwei Fan, Liren Yang, Xi Hu, Ruihan Luo, Yankai Yu, Sophia Li, Weiling Zhao, Xiaobo Zhou   +11 more
wiley   +1 more source

Adaptive traffic signal control using deep reinforcement learning: Toward smarter and safer urban mobility. [PDF]

PLoS One
Alanazi F, Armghan A, Tanveer M, Yousef A.   +3 more
europepmc   +1 more source

Cis‐ and Trans‐Regulatory Factors Independently Shape Phenotypic Heterogeneity of Retinitis Pigmentosa

Advanced Science, EarlyView.
A zebrafish model carrying an identical human RHO S334X allele reveals two independent genetic layers shaping retinitis pigmentosa (RP) severity: a protective 3‐bp cis‐regulatory insertion that attenuates transgene expression, and a dominant trans‐acting modifier that restores a severe phenotype.
Cong Cui, Kotone Nakagawa, Takumi Tateno, Ayaka Dan, Dexin Meng, Yoshihiro Omori, Soma Tomihara, Suzuri Okamoto, Shigeru Sato, Motokazu Tsujikawa   +9 more
wiley   +1 more source

Network traffic control method of NHP based on deep reinforcement learning. [PDF]

Sci Rep
Huang Q, Tan Z, Wang Q, Jia Z, Chen B.
europepmc   +1 more source

An Integrated NLP‐ML Framework for Property Prediction and Design of Steels

Advanced Science, EarlyView.
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju, Adithya Umanath Rai, Jose Thomson, Marzie Ghorbani, Shujing Zhao, Nick Birbilis   +5 more
wiley   +1 more source

Deep Reinforcement Learning for Secure and Low-Latency Communications in UAV-Mounted STAR-RIS Assisted Urban Vehicular Networks. [PDF]

Sensors (Basel)
Tang J, Yuan J, Zhao H, Chen M, Peng Y.
europepmc   +1 more source