Results 211 to 220 of about 6,652,811 (287)

Fully memristive spiking neural network for energy-efficient graph learning. [PDF]

Sci Adv
Shi T, Gao L, Zhou R, Tian Y, Chen P, Ding Y, Tang S, Ma H, Lu J, Zhang H, Wang Z, Lyu B, Zhang X, Yan X, Liu Q.   +14 more
europepmc   +1 more source

S3RL: Enhancing Spatial Single‐Cell Transcriptomics With Separable Representation Learning

Advanced Science, EarlyView.
Separable Spatial Representation Learning (S3RL) is introduced to enhance the reconstruction of spatial transcriptomic landscapes by disentangling spatial structure and gene expression semantics. By integrating multimodal inputs with graph‐based representation learning and hyperspherical prototype modeling, S3RL enables high‐fidelity spatial domain ...
Laiyi Fu, Penglei Wang, Gaoyuan Xu, Jitao Lu, Qinke Peng, Danyang Wu, Hequan Sun   +6 more
wiley   +1 more source

Quantifying extreme failure scenarios in transportation systems with graph learning. [PDF]

Patterns (N Y)
Guo M, Zhao T, Gao J, Meng X, Gao Z.
europepmc   +1 more source

In Situ X‐Ray Tomography and Acoustic Emission Monitoring of Damage Evolution in C/C‐SiC Composites Fabricated by Liquid Silicon Infiltration

Advanced Science, EarlyView.
This study investigates how the internal structure of fiber‐reinforced ceramic composites affects their resistance to damage. By combining 3D X‐ray imaging with acoustic emission monitoring during mechanical testing, it reveals how silicon distribution influences crack formation.
Yang Chen, Renato S. M. Almeida, Stefan Flauder, Guillaume Couégnat, Kamen Tushtev, Jürgen Horvath, Peter Wriggers, Kurosch Rezwan   +7 more
wiley   +1 more source

Non-end-to-end adaptive graph learning for multi-scale temporal traffic flow prediction. [PDF]

PLoS One
Xu K, Pan B, Zhang M, Zhang X, Hou X, Yu J, Lu Z, Zeng X, Jia Q.   +8 more
europepmc   +1 more source

Unveil Fundamental Graph Properties for Neural Architecture Search

Advanced Science, EarlyView.
This paper proposes NASGraph, a graph‐based framework that represents neural architectures as graphs whose structural properties determine performance. By revealing structure–performance relationships, NASGraph enables efficient neural architecture search with significantly reduced computation.
Zhenhan Huang, Tejaswini Pedapati, Pin‐Yu Chen, Chunheng Jiang, Jianxi Gao   +4 more
wiley   +1 more source

Molecule generation for drug design: A graph learning perspective. [PDF]

Fundam Res
Yang N, Wu H, Zeng K, Li Y, Bao S, Yan J.   +5 more
europepmc   +1 more source

A Wireless, Battery‐Free Artificial Throat Patch with Deep Learning for Emotional Speech Recognition

Advanced Science, EarlyView.
In this work, Xu and co‐workers develop a wireless, battery‐free artificial throat patch system (ATPS) consisting of a carbon nanotube‐based thin‐film strain sensor and a miniaturized flexible printed circuit board, to enable real‐time sensing of throat signals.
Bingxin Xu, Guanming Lin, Xiaohui Hong, Chuting Liu, Xinyi Qu, Kangjian Jiao, Lei Zhang, Bingzhe Xu, Jun Yan, Yancong Qiao, Xudong Lin   +10 more
wiley   +1 more source

Deep Learning‐Powered Scalable Cancer Organ Chip for Cancer Precision Medicine

Advanced Science, EarlyView.
This scalable, low‐cost Organ Chip platform, made via injection molding, uses capillary pinning for hydrogel confinement and supports versatile tissue coculture and robust imaging. Deep learning enables label‐free, sensitive phenotypic analysis.
Yu‐Chieh Yuan, Beibei Xu, Jenna McCormack, XuHai Huang, Jingzhe Ma, Thomas Marshall, Yacong Sun, Hardeep Singh, Alyssa Fanelli, Gauri Kulkarni, Ji Hye Seo, Paige Gilbride, Bing Wei, Bo Wang, Yanyan Liu, Fei Ma, Lin Zhou, Shuyang Wang, Xiaohua Qian, Zhiyong Xie, Polina Golland, Longlong Si, Yu Shrike Zhang, Xin Xie, Haiqing Bai   +24 more
wiley   +1 more source

A Knowledge-Guided Graph Learning Approach Bridging Phenotype- and Target-Based Drug Discovery. [PDF]

Adv Sci (Weinh)
Ye Q, Zeng Y, Jiang L, Kang Y, Pan P, Chen J, Deng Y, Zhao H, He S, Hou T, Hsieh CY.   +10 more
europepmc   +1 more source