Simulation & Optimization: Poisson Process & Random Numbers

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Covers fundamental concepts in probability and statistics, including distributions, properties, and expectations of random variables.

Probability Theory: Midterm Solutions

Covers the solutions to the midterm exam of a Probability Theory course, including calculations of probabilities and expectations.

Monte-Carlo Integration

Covers Monte-Carlo integration, simulation, and transforming draws from different distributions.

Nonuniform Random Number Distributions: Examples and Methods

Explores nonuniform random number distributions, examples, methods, and generation techniques.

Data reconciliation and parameter identification by FM

Explores measurement analysis, data reconciliation, and parameter identification in energy systems, emphasizing the importance of correct measurements and optimization.

Estimating R: Moments of a Distribution

Explains the importance of moments in measuring distribution properties, such as expectation and variance.

Probability Theory: Central Limit Theorem

Explores probability theory, distribution of averages, and the central limit theorem.

Rainfall Models: Deterministic vs Stochastic

Covers deterministic and stochastic rainfall models in water resources engineering, including generation, calibration, and spatially explicit models.

Quantum Random Number Generation

Explores quantum random number generation, discussing the challenges and implementations of generating good randomness using quantum devices.

Quantum Jump: Theory and Algorithms

Explores the theory of quantum jumps in open quantum systems and their simulation.