Sampling from probability distributions with known density functions (up to normalization) is a fundamental challenge across various scientific domains. From Bayesian uncertainty quantification to ...

Many complex systems can be modeled via Markov jump processes. Applications include chemical reactions, population dynamics, and telecommunication networks. Rare-event estimation for such models can ...

This project explores sampling from a 2D Gaussian distribution using Python libraries Numpy and Matplotlib. Key tasks include: Drawing 100 samples from a Gaussian distribution with a mean of [0, 0] ...