eLife

Predicting human decision-making across task conditions via individuality transfer

Encoding individual behavioral traits into a low-dimensional latent representation enables the accurate prediction of decision-making patterns across distinct task conditions.
IEEE

An Optimized Model With Encoder-Decoder ConvLSTM for Global Ionospheric Forecasting

Abstract: The ionosphere is vital for satellite navigation and radio communication, but observational limitations necessitate ionospheric forecasting. The least squares collocation (LSC) method is ...
IEEE

CGM-Based Blood Glucose Prediction Model With LSTM Encoder–Decoder Architecture

Abstract: Accurate prediction of blood glucose levels is crucial for automated treatment in diabetic patients. This study proposes a blood glucose prediction model based on an improved attention ...
Frontiers

Beyond the amyloid hypothesis: Leveraging human-centered complex in vitro models to decode Alzheimer's disease etiology

The final, formatted version of the article will be published soon. Alzheimer's disease (AD) is a complex neurodegenerative condition and the leading cause of dementia worldwide. Treatments that ...
GitHub

Sequential Graph-Based Decoding of the Surface Code using a Hybrid Graph and Recurrent Neural Network Model

This Git repo contains simplified source code for creating and testing our combined graph neural network and recurrent neural network used for decoding the surface code.
조선일보

Naver faces criticism over using Chinese encoder in national AI model project

Deputy Prime Minister and Minister of the Ministry of Science and ICT Bae Kyung-hoon, Ha Jung-woo, Senior Secretary for AI Future Planning at the Presidential Office, and other attendees pose for a ...