Scientific Research Publishing

Traffic Speed Prediction Based on Autoencoder and Deep Learning ()

Traffic prediction is the core of intelligent transportation system, and accurate traffic speed prediction is the key to optimize traffic management. Currently, the traffic speed prediction model ...
Frontiers

Deep learning radiomics nomogram predicts lymph node metastasis in laryngeal squamous cell carcinoma

Background: Lymph node metastases (LNM) in laryngeal squamous cell carcinoma (LSCC) has been associated with lower survival, but current imaging methods, such as computed tomography (CT), have limited ...
GitHub

sparse-autoencoder

Add a description, image, and links to the sparse-autoencoder topic page so that developers can more easily learn about it.
Phys.org

Using geometry and physics to explain feature learning in deep neural networks

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...
blockchain

Mechanistic Faithfulness in AI: Key Debate in Sparse Autoencoder Interpretability According to Chris Olah

According to Chris Olah, the central issue in the ongoing Sparse Autoencoder (SAE) debate is mechanistic faithfulness, which refers to how accurately an interpretability method reflects the internal ...
Scientific Research Publishing

Traffic Speed Prediction Based on Autoencoder and Deep Learning ()

College of Mathematics and Statistics, Northwest Normal University, Lanzhou, China. Traffic prediction is the core of intelligent transportation system, and accurate traffic speed prediction is the ...
Frontiers

BANSMDA: a computational model for predicting potential microbe-disease associations based on bilinear attention networks and sparse autoencoders

Introduction: Predicting the relationship between diseases and microbes can significantly enhance disease diagnosis and treatment, while providing crucial scientific support for public health, ...
IEEE

Joint Sparse Autoencoder Based Massive MIMO CSI Feedback

Abstract: In frequency division duplex (FDD) based massive multiple-input multiple-output (MIMO) systems, the channel state information (CSI) feedback overhead could degrade spectrum and energy ...