UQpy (Uncertainty Quantification with python) is a general purpose Python toolbox for modeling uncertainty in physical and mathematical systems.
-
Updated
Oct 4, 2024 - Python
UQpy (Uncertainty Quantification with python) is a general purpose Python toolbox for modeling uncertainty in physical and mathematical systems.
Repository for the final project for Procesos Estocásticos. S1.63.10
Model of propagating blobs in 1D and 2D
The offcial implementation of the Moment Neural Network (MNN)
A library for discrete-time Markov chains analysis.
kramersmoyal: Kramers-Moyal coefficients for stochastic data of any dimension, to any desired order
Pieces of code that have appeared on my blog with a focus on stochastic simulations.
A tiny package to compute the dynamics of stochastic and molecular simulations
Simulation for deep reinforcement learning on stochastic time series
Python scripts based on Dobrow's "Introduction to Stochastic Processes with R"
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.
This code belongs to ACL conference paper entitled as "An Online Semantic-enhanced Dirichlet Model for Short Text Stream Clustering"
The code that powers my thesis
Python implementation of fractional brownian motion
for modeling random walks: https://en.wikipedia.org/wiki/Random_walk
The Coastal version of the Stochastic Multcloud model
Add a description, image, and links to the stochastic-process topic page so that developers can more easily learn about it.
To associate your repository with the stochastic-process topic, visit your repo's landing page and select "manage topics."