Ecosyste.ms: Repos

An open API service providing repository metadata for many open source software ecosystems.

GitHub topics: variance-reduction

Repositories

NVIDIA/framework-reproducibility

Providing reproducibility in deep learning frameworks

Language: Python - Size: 1.19 MB - Last synced: 7 days ago - Pushed: 15 days ago - Stars: 419 - Forks: 39

jonathf/chaospy

Chaospy - Toolbox for performing uncertainty quantification.

Language: Python - Size: 54.4 MB - Last synced: about 1 month ago - Pushed: 12 months ago - Stars: 427 - Forks: 85

jerryxyx/MonteCarlo

A model free Monte Carlo approach to price and hedge American options equiped with Heston model, OHMC, and LSM

Language: Jupyter Notebook - Size: 2.11 MB - Last synced: 3 months ago - Pushed: about 5 years ago - Stars: 92 - Forks: 51

mbsuraj/stationarityToolkit

Statistical toolkit to make time-series stationary

Language: Python - Size: 9.77 KB - Last synced: 17 days ago - Pushed: 7 months ago - Stars: 0 - Forks: 0

caramel2001/Financial-Derivative-Analysis-and-Simulation

Pricing and Analysis of Financial Derivative by Credit Suisse using Monte Carlo, Heston Model, CIR model, estimating greeks such as delta, gamma etc, Local volatility model incorporated with variance reduction.(For MH4518 Project)

Language: Jupyter Notebook - Size: 18.3 MB - Last synced: 4 months ago - Pushed: 9 months ago - Stars: 17 - Forks: 3

thorpn/MonteCarlo

Monte Carlo used for the seminar Monte Carlo Methods in Econometrics and Finance at the university of Copenhagen

Language: MATLAB - Size: 85 KB - Last synced: 4 months ago - Pushed: about 1 year ago - Stars: 1 - Forks: 2

Adamdad/Filter-Gradient-Decent

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.

Language: Python - Size: 1.22 MB - Last synced: 15 days ago - Pushed: about 3 years ago - Stars: 11 - Forks: 2

YiSyuanChen/Averaged-DQN

Reproduced PyTorch implementation for ICML 2017 Paper "Averaged-DQN: Variance Reduction and Stabilization for Deep Reinforcement Learning."

Language: Python - Size: 64.4 MB - Last synced: 7 months ago - Pushed: almost 3 years ago - Stars: 1 - Forks: 0

slowbull/MPIPlatform

A platform for distributed optimization expriments using OpenMPI

Language: C++ - Size: 31.9 MB - Last synced: 7 months ago - Pushed: over 6 years ago - Stars: 20 - Forks: 11

hiroyuki-kasai/SGDLibrary

MATLAB/Octave library for stochastic optimization algorithms: Version 1.0.20

Language: MATLAB - Size: 31.3 MB - Last synced: 7 months ago - Pushed: about 1 year ago - Stars: 194 - Forks: 87

rockstaedt/ses_opt

Framework to model two stage stochastic unit commitment optimization problems.

Language: Python - Size: 83.6 MB - Last synced: 4 months ago - Pushed: about 3 years ago - Stars: 9 - Forks: 3

Jspano95/Derivatives_Pricing_Models

Introduction to options pricing theory and advanced numerical methods for pricing both vanilla and exotic options.

Language: Jupyter Notebook - Size: 153 KB - Last synced: 7 months ago - Pushed: about 3 years ago - Stars: 6 - Forks: 4

anthonyli01/R-Derivatives-Pricing

University Project: simulation techniques to price derivatives. It will involve Monte-Carlo, variance-reduction techniques, and advanced simulation methods.

Size: 1.38 MB - Last synced: 9 months ago - Pushed: almost 2 years ago - Stars: 0 - Forks: 0

anthonyli01/Advanced-Simulation-Methods

This project focuses on applying advanced simulation methods for derivatives pricing. It includes Monte-Carlo, Variance Reduction Techniques, Distribution Sampling Methods, Euler Schemes, and Milstein Schemes.

Language: Jupyter Notebook - Size: 1.37 MB - Last synced: 4 months ago - Pushed: 9 months ago - Stars: 0 - Forks: 1

agadetsky/pytorch-pl-variance-reduction

Low-variance Black-box Gradient Estimates for the Plackett-Luce Distribution, AAAI 2020 and NeurIPS 2019 Bayesian Deep Learning Workshop

Language: Jupyter Notebook - Size: 410 KB - Last synced: 10 months ago - Pushed: over 3 years ago - Stars: 35 - Forks: 2

WayneDW/Variance_Reduced_Replica_Exchange_SGMCMC

Variance reduction in energy estimators accelerates the exponential convergence in deep learning (ICLR'21)

Language: C - Size: 265 MB - Last synced: 12 months ago - Pushed: over 1 year ago - Stars: 8 - Forks: 3

JRigh/Importance-sampling-in-R

Importance sampling in R course notes and code

Language: R - Size: 197 KB - Last synced: 4 months ago - Pushed: about 1 year ago - Stars: 0 - Forks: 0

mhw32/antithetic-vae-public

PyTorch implementation for " Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference" (https://arxiv.org/abs/1810.02555).

Language: Python - Size: 750 KB - Last synced: 2 months ago - Pushed: over 5 years ago - Stars: 6 - Forks: 0

hiroyuki-kasai/SimpleDeepNetToolbox

Simple MATLAB toolbox for deep learning network: Version 1.0.3

Language: Matlab - Size: 83 KB - Last synced: about 1 year ago - Pushed: about 5 years ago - Stars: 16 - Forks: 10

mingzhang-yin/ARM-gradient

Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)

Language: Python - Size: 43.5 MB - Last synced: about 1 year ago - Pushed: about 5 years ago - Stars: 27 - Forks: 9

hiroyuki-kasai/RSOpt

Riemannian stochastic optimization algorithms: Version 1.0.3

Language: MATLAB - Size: 7.62 MB - Last synced: about 1 year ago - Pushed: over 1 year ago - Stars: 51 - Forks: 19

piers-hinds/sde_mc

Numerical integration of SDEs with variance reduction methods for Monte Carlo simulation

Language: Python - Size: 5.49 MB - Last synced: about 1 year ago - Pushed: about 1 year ago - Stars: 2 - Forks: 0

EliaFantini/FO-PROX-first-order-and-proximal-methods-convergence-comparison

Implementation and brief comparison of different First Order and different Proximal gradient methods, comparison of their convergence rates

Language: Python - Size: 4.35 MB - Last synced: about 1 year ago - Pushed: over 1 year ago - Stars: 0 - Forks: 0

anthonytedja/teams

teams partitions players into equal teams with minimum variance

Language: Python - Size: 2.93 KB - Last synced: about 1 year ago - Pushed: almost 2 years ago - Stars: 0 - Forks: 0

dmivilensky/Sliding-for-Kernel-SVM

We consider a problem of minimizing a sum of two functions and propose a generic algorithmic framework (SAE) to separate oracle complexities for each function. We compare the performance of splitting accelerated enveloped accelerated variance reduced method with a different sliding technique.

Language: Jupyter Notebook - Size: 267 KB - Last synced: about 1 year ago - Pushed: over 2 years ago - Stars: 0 - Forks: 0