GitHub

CPA - Compositional Perturbation Autoencoder

CPA is a framework to learn the effects of perturbations at the single-cell level. CPA encodes and learns phenotypic drug responses across different cell types, doses, and combinations. CPA allows: ...
IEEE

ASHSniper: Automatic One-shot Hyperparameter Selection for Density Peaks Clustering

Abstract: Clustering is essential in data analysis since many real-world datasets are unlabeled and are expensive to label. Density-based clustering algorithms are known for their capability of ...
IEEE

Understanding Code Smell Detection Through Hyperparameter Optimization and Metric Correlation Analysis

Abstract: Hyperparameter optimization plays a pivotal role in the reliability and generalization of machine-learning models for software quality prediction. This paper presents a comparative ...
GitHub

Generating realistic neurophysiological time series with denoising diffusion probabilistic models

Code for the paper "Generating realistic neurophysiological time series with denoising diffusion probabilistic models", (2024). The repository contains all the scripts to run the experiments presented ...
eWeek

AI Model Optimization: 6 Key Techniques

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...
C&EN

Optimizing Hyperparameter Tuning in Machine Learning to Improve the Predictive Performance of Cross-Species N6-Methyladenosine Sites

Professional Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, Taipei 110, Taiwan Research Center for Artificial Intelligence in Medicine, Taipei ...