ABSTRACT: This paper investigates the application of machine learning techniques to optimize complex spray-drying operations in manufacturing environments. Using a mixed-methods approach that combines ...

1 Minutia.AI Pte. Ltd., Singapore, Singapore 2 Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milano, Italy A representation of the cause-effect mechanism is ...

Heterogeneity among experimental units can introduce experimental errors, necessitating the use of techniques that enhance statistical inferences to address this ...

Based on the compounding mechanism, a unique discrete probability distribution is investigated in this paper. The Poisson distribution is mixed with a lifetime model called as the Fav-Jerry model. The ...

Mathematics Department, Egerton University, Njoro Nakuru, Kenya. Bayesian techniques have been applied in many epidemiological settings, such as disease monitoring, outbreak simulation, and prevalence ...

This paper provides an important proposal for why learning can be much faster and more accurate if synapses have a fast component that immediately corrects errors, as well as a slower component that ...

This repository represents my work through out the "Robotics: Estimation and Learning" course offered by University of Pennsylvania which is available on Coursera online learning platform.

Learned the fundamentals and applications in ML: Intro to Prob. & Linear algebra, Decision Theory, MLE & BE, Linear Model, Linear Discriminant function, Perceptron, FLD, PCA, Non-parametric Learning, ...

The mathematics that enable sensor fusion include probabilistic modeling and statistical estimation using Bayesian inference and techniques like particle filters, Kalman filters, and α-β-γ filters, ...