IEEE

A Survey on Deep Reinforcement Learning Applications in Autonomous Systems: Applications, Open Challenges, and Future Directions

Abstract: Deep Reinforcement Learning (DRL) has become a fundamental element in advancing Autonomous Systems, significantly transforming fields like autonomous vehicles, robotics, and drones. This ...
Scientific Research Publishing

James, G., Witten, D., Hastie, T. and Tibshirani, R. (2013) An Introduction to Statistical Learning. Springer.

ABSTRACT: Riverbank instability poses a mounting global threat, especially across East Africa’s transboundary river systems, where geospatial assessments remain scarce. This study applies advanced ...
Ohio University

Applications now open for Experiential Learning Funds

The Fall application period is now open for Ohio University’s Experiential Learning Awards. Undergraduate students, faculty and staff from all OHIO campuses are invited to apply for Experiential ...
Scientific Research Publishing

Applications of Non-Equilibrium Thermodynamics and Statistical Mechanics of Vortex Gases in Tornado Theory ()

1 Department of Mathematics, Computer Science, and Data Science, Augsburg University, Minneapolis, MN, USA. 2 Department of Mathematics, University of St. Thomas, St. Paul, MN, USA. A recent numerical ...
IEEE

An Explainable Unified Framework of Spatio-Temporal Coupling Learning With Application to Dynamic Brain Functional Connectivity Analysis

Abstract: Time-series data such as fMRI and MEG carry a wealth of inherent spatio-temporal coupling relationship, and their modeling via deep learning is essential for uncovering biological mechanisms ...
GitHub

Introduction to Statistical Learning and Applications

The goal of this course is to introduce students to classical approaches of statistical learning. The information age has resulted in masses of multivariate data in many fields: finance, marketing, ...