Mînzu, V. and Arama, I. (2025) A New Method to Predict the Mechanical Behavior for a Family of Composite Materials. Journal ...

Understanding the neural mechanisms underlying associative threat learning is essential for advancing behavioral models of threat and adaptation. We investigated distinct activation patterns across ...

This paper would be of interest to researchers studying cognitive control and adaptive behavior, if the concerns raised in the reviews can be addressed satisfactorily. Understanding how task knowledge ...

Abstract: This paper is centered around the approximation of dynamical systems by means of Gaussian processes. To this end, trajectories of such systems must be collected to be used as training data.

This project covers comprehensive regression analysis including Linear Regression, Polynomial Regression, Model Selection, and Gaussian Process Regression with LIDAR data analysis. Advanced_ML_Project ...

Estimating time-varying signals becomes particularly challenging in the face of non-Gaussian (e.g., sparse) and/or rapidly time-varying process noise. By building upon the recent progress in the ...

Department of Materials Science and Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea Graduate School of Semiconductor Materials and Devices ...