Here are
24 public repositories
matching this topic...
Chaospy - Toolbox for performing uncertainty quantification.
Updated
Aug 4, 2021
Python
MATLAB/Octave library for stochastic optimization algorithms: Version 1.0.20
Updated
Jun 8, 2021
MATLAB
A model free Monte Carlo approach to price and hedge American options equiped with Heston model, OHMC, and LSM
Updated
Apr 5, 2019
Jupyter Notebook
Riemannian stochastic optimization algorithms: Version 1.0.3
Updated
Jun 10, 2021
MATLAB
Low-variance Black-box Gradient Estimates for the Plackett-Luce Distribution, AAAI 2020 and NeurIPS 2019 Bayesian Deep Learning Workshop
Updated
Jan 12, 2021
Jupyter Notebook
Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)
Updated
Mar 9, 2019
Python
A platform for distributed optimization expriments using OpenMPI
Simple MATLAB toolbox for deep learning network: Version 1.0.3
Updated
Apr 16, 2019
MATLAB
Updated
Dec 29, 2018
Python
Variance reduction in energy estimators accelerates the exponential convergence in deep learning (ICLR'21)
Chance-constrained control and pricing for natural gas networks using Julia/JuMP.
Updated
May 12, 2021
Julia
Stochastic Simulation and Statistics in Tidyverse
Updated
Dec 11, 2020
Jupyter Notebook
In this paper, we propose Filter Gradient Decent (FGD), an efficient stochastic optimization algorithm that makes a consistent estimation of the local gradient by solving an adaptive filtering problem with different designs of filters.
Updated
May 18, 2021
Python
An R Library published on CRAN for variance reduction algorithms.
Updated
Oct 24, 2017
Python
My Master's Thesis on Variational Optimization of Neural Networks written at the Technical University of Denmark
Updated
Dec 15, 2017
Jupyter Notebook
Project on using control variates for bayesian neural networks
Updated
Jan 29, 2021
Jupyter Notebook
Updated
Sep 20, 2018
Jupyter Notebook
Framework to model two stage stochastic unit commitment optimization problems.
Updated
Apr 28, 2021
Python
Training a single layer perceptron model on sparse data (coursework)
Introduction to options pricing theory and advanced numerical methods for pricing both vanilla and exotic options.
Updated
May 1, 2021
Jupyter Notebook
Weak-sense numerical integration of SDEs with variance reduction methods for Monte Carlo simulation
Updated
Sep 14, 2021
Python
a simple implementation of gradient domain path tracing
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