Abstract: Deterministic Turing machines and their associated complexity measures, by construction, cannot capture the complexity of the output of stochastic processes - like those in the real world.

Abstract: Near-infrared (NIR) technology has gained wide acceptance in practical processes and is now the measurement of choice in many sectors. However, with increasing spectral dimensionality, it is ...

This project provides an interactive Streamlit application for simulating and visualizing two important stochastic processes: the Poisson process and the Merton Jump Diffusion Model. Users can explore ...

Abstract: Distributed Learning is pivotal for training extensive deep neural networks across multiple nodes, leveraging parallel computation to hasten the learning process. However, it faces ...

The development of this work is described fully in the following work, cited as: @phdthesis{chan2023thesis, author = "Moses Y.-H. Chan", title = "High-Dimensional Gaussian Process Methods for ...

This study infers probabilistic infection routes of a vector-borne disease, by modeling internal dynamics of metapopulations driven by human mobility as multivariate stochastic processes. In this way, ...