1.4k citations · 1.8k across the 5 of their papers we have counts for
5 papers
Towards Human-interpretable Explanation in Code Clone Detection using LLM-based Post Hoc Explainer
Teeradaj Racharak, Chaiyong Ragkhitwetsagul, Chayanee Junplong +1
Recent studies highlight various machine learning (ML)-based techniques for code clone detection, which can be integrated into developer tools such as static code analysis. With th…
Quantifying the Impact of Data Characteristics on the Transferability of Sleep Stage Scoring Models
Akara Supratak, Peter Haddawy
Deep learning models for scoring sleep stages based on single-channel EEG have been proposed as a promising method for remote sleep monitoring. However, applying these models to ne…
TensorLayer: A Versatile Library for Efficient Deep Learning Development
Hao Dong, Akara Supratak, Luo Mai +4
Deep learning has enabled major advances in the fields of computer vision, natural language processing, and multimedia among many others. Developing a deep learning system is arduo…
DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG
Akara Supratak, Hao Dong, Chao Wu +1
The present study proposes a deep learning model, named DeepSleepNet, for automatic sleep stage scoring based on raw single-channel EEG. Most of the existing methods rely on hand-e…
Mixed Neural Network Approach for Temporal Sleep Stage Classification
Hao Dong, Akara Supratak, Wei Pan +3
This paper proposes a practical approach to addressing limitations posed by use of single active electrodes in applications for sleep stage classification. Electroencephalography (…