UQpy (Uncertainty Quantification with python) is a general purpose Python toolbox for modeling uncertainty in physical and mathematical systems.
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Updated
Oct 4, 2024 - Python
UQpy (Uncertainty Quantification with python) is a general purpose Python toolbox for modeling uncertainty in physical and mathematical systems.
Pieces of code that have appeared on my blog with a focus on stochastic simulations.
A library for discrete-time Markov chains analysis.
kramersmoyal: Kramers-Moyal coefficients for stochastic data of any dimension, to any desired order
Python implementation of fractional brownian motion
A tiny package to compute the dynamics of stochastic and molecular simulations
This code belongs to ACL conference paper entitled as "An Online Semantic-enhanced Dirichlet Model for Short Text Stream Clustering"
Model of propagating blobs in 1D and 2D
The Coastal version of the Stochastic Multcloud model
Basic discrete event simulation of a queuing system. This simulation can be used as a basis for most other types of discrete-event simulations. This version is an example that simulates a G/G/c queuing system.
The code that powers my thesis
Repository for the final project for Procesos Estocásticos. S1.63.10
Python scripts based on Dobrow's "Introduction to Stochastic Processes with R"
The offcial implementation of the Moment Neural Network (MNN)
for modeling random walks: https://en.wikipedia.org/wiki/Random_walk
Simulation for deep reinforcement learning on stochastic time series
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