Results 101 to 110 of about 60,311 (308)

The structure of an autoencoder.

, 2019
The structure of an autoencoder.
Yaru Hao (6593603), Xue Hu (3309012), Lili Chen (66681)   +2 more
core   +1 more source

STWave: Fine‐Scale Spatial Structure Discovery in Microscopic‐Resolution Spatial Transcriptomics via Patchwise Wavelet Graphs

Advanced Science, EarlyView.
STWave transforms massive microscopic‐resolution spatial transcriptomics into interpretable fine‐scale tissue maps through patch‐wise inference, wavelet‐based multi‐scale encoding, and dual‐domain reconstruction. It reduces noise while preserving weak spatial signals, enabling efficient analysis of 6 40 000 spots of 2.47 GB GPU memory and revealing ...
Tao Jiang, Songming Zhang, Xiaofeng Chen, Xiongtao Xiao, Wenming Cao, Weikai Li, Tong Zhao, Bing Li, Xinyue Xu, Zhongshan Li   +9 more
wiley   +1 more source

Composite Denoising Autoencoders [PDF]

, 2016
In representation learning, it is often desirable to learn features at different levels of scale. For example, in image data, some edges will span only a few pixels, whereas others will span a large portion of the image. We introduce an unsupervised representation learning method called a composite denoising autoencoder CDA to address this.
Geras, Krzysztof, Sutton, Charles
openaire   +2 more sources

The Attention Enhanced Autoencoder for Balise Anomaly Detection in Potting Process

IEEE Access
Balise is a critical trackside component in railway systems, operating in harsh environments where silicone gel potting enhances reliability. However, the potting process is irreversible; defects lead to costly scrap and operational delays.
Ke Ye, Jingpin Jiao, Fanghua Chen, Qing Xu, Gehui Liu, Jun Wang   +5 more
doaj   +1 more source

Uncoupling Type I Interferon Benefits From Inflammatory Toxicity: Transformer‐Prioritized Precision Agonists for Potent and Safer Cancer Immunotherapy

Advanced Science, EarlyView.
A Transformer‐based AI framework, DLINP, screens millions of compounds to identify Co68, a cobalt‐pincer organometallic complex that biases TLR4‐MD2 signaling toward antitumor interferon activation while suppressing inflammatory toxicity through an early TLR4‐SYK‐STAT1 axis.
Xuefei Guo, Yang Zhao, Xianle Rong, Xingyu Chen, Xiao Wang, Tianyi Liu, Yunfei Xie, Yushu Zou, Pingsen Zhao, Qiang Liu, Fuping You   +10 more
wiley   +1 more source

Deep-Learning Approach for an Analysis of Real-Estate Prices and Transactions

IEEE Access
Research on the study of houses, condominiums and buildings in Taiwan’s metropolitan areas continues to be an important area of research. In real estate forecasting and analysis, methods such as statistical analysis and questionnaire data ...
Cheng-Hong Yang, Borcy Lee, Yu-Da Lin
doaj   +1 more source

Predicting Single‐Cell Perturbation Responses Across Biological Contexts With a Deep Generative Model Integrating Optimal Transport

Advanced Science, EarlyView.
Single‐cell perturbation responses are predicted across held‐out biological contexts using scPILOT, a query‐conditioned two‐stage latent response‐transfer framework. A shared latent representation supports cell‐level response estimation by latent optimal transport, followed by Leiden‐localized query‐specific transfer and adaptive weighting.
Jialiang Wang, Ziqi Liu, Zhengqian Zhang, Yikun Cao, Junjun Ren, Peng Cheng, Jingjing Tian, Lingyun Xie, Xin Lu, Zhanwei Du, Yongzhuang Liu   +10 more
wiley   +1 more source

Synthesizing Time-Series Gene Expression Data to Enhance Network Inference Performance Using Autoencoder

Applied Sciences
It is a challenge to infer a gene regulatory network from time-series gene expression data in the systems biology field. A lack of gene expression data samples is a factor limiting the performance of the inference methods.
Cao-Tuan Anh, Yung-Keun Kwon
doaj   +1 more source

Autoencoder for Meander Bends Classification

Trained convolutional autoencoder from the paper "A Curvature-Based Framework for Automated Classification of Meander Bends"Lopez Dubon, S., Sgarabotto, A., & Lanzoni, S. (2024). Autoencoder for Meander Bends Classification. Zenodo.
Sgarabotto, Alessandro, Lanzoni, Stefano, School of Engineering, Lopez Dubon, Sergio; id_orcid   +3 more
core   +1 more source

Autoencoder variability.

, 2023
Variability of the shallow autoencoder on the Sim1 dataset (17 clusters) over 100 executions, where the white star represents the average score over 100. An important note is that DBS has lower scores for a higher performance and as DBS and CHS have only
Ana-Maria Ichim (14648702), Raul Cristian Mureșan (14769090), Andreea Coporîie (14769084), Mihaela Dînșoreanu (14769087), Eugen-Richard Ardelean (14648699)   +4 more
core   +1 more source