This page collects a few answers to questions that have frequently been asked about deal.II and that we thought are worth recording as they may be useful to others as well. This used to be one of the ...
We consider the problem of fitting a reinforcement learning (RL) model to some given behavioral data under a multi-armed bandit environment. These models have received much attention in recent years ...
ABSTRACT: This paper deals with linear programming techniques and their application in optimizing lecture rooms in an institution. This linear programming formulated based on the available secondary ...
Intelligent vehicles and autonomous driving have been the focus of research in the field of transport, but current autonomous driving models have significant errors in lateral tracking that cannot be ...
The Kampmann–Wagner Numerical (KWN) model of precipitation is a powerful tool to simulate the precipitation of the second phase considering the nucleation, growth, and coarsening. Some quantities such ...
Professor Liz Bentley, Chief Executive of the Royal Meteorological Society, will deliver the 2025 Distinguished Annual Edith Morley Seminar on Thursday 30th April at 3:00pm in Room 109, Palmer ...
Corneal opacities are important causes of blindness, and their major etiology is infectious keratitis. Slit-lamp examinations are commonly used to determine the causative pathogen; however, their ...
Center on Stochastic Modeling, Optimization, and Statistics (COSMOS), The University of Texas at Arlington, Arlington, TX, USA. Quantitative decision analysis involves notions of comparison and ...
An increasing number of population genomic studies now try to infer complex models of population history using a number of whole-genome sequences sampled from multiple populations. A key technical ...
Worse-case analysis takes a “Murphy’s Law” approach to algorithm analysis, which is too crude to give meaningful algorithmic guidance for many important problems, including linear programming, ...
Algorithms are pre-defined, self-contained sets of instructions designed to execute diverse functions, and they have been around for longer than you might expect. From ancient Babylon to the present ...
Deep reinforcement learning was employed to optimize chemical reactions. Our model iteratively records the results of a chemical reaction and chooses new experimental conditions to improve the ...
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