GitHub topics: variance-reduction

Repositories

Yixing-Shen/Monte_Carlo

Monte Carlo option pricing experiments under the Black-Scholes model using variance reduction techniques.

Language: Jupyter Notebook - Size: 418 KB - Last synced at: 4 days ago - Pushed at: 5 days ago - Stars: 0 - Forks: 0

NVIDIA/framework-reproducibility

Providing reproducibility in deep learning frameworks

Language: Python - Size: 1.19 MB - Last synced at: 1 day ago - Pushed at: 11 months ago - Stars: 427 - Forks: 38

amazon-science/mezo_svrg

Code the ICML 2024 paper: "Variance-reduced Zeroth-Order Methods for Fine-Tuning Language Models"

Language: Python - Size: 96.7 KB - Last synced at: 14 days ago - Pushed at: 10 months ago - Stars: 10 - Forks: 0

rockstaedt/ses_opt

Framework to model two stage stochastic unit commitment optimization problems.

Language: Python - Size: 83.6 MB - Last synced at: 3 days ago - Pushed at: almost 4 years ago - Stars: 14 - Forks: 3

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 at: 26 days ago - Pushed at: about 6 years ago - Stars: 107 - Forks: 52

repositony/mesh2ww

Command line tool to generate mesh-based weight windows. Supports all MCNPv6.2 legacy meshtal output formats for rectangular and cylindrical meshes.

Language: Rust - Size: 65.4 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

jiedxu/TidySimStat

Stochastic Simulation and Statistics in Tidyverse

Language: Jupyter Notebook - Size: 102 MB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 2 - Forks: 1

mbsuraj/stationarityToolkit

Statistical toolkit to make time-series stationary

Language: Python - Size: 12.7 KB - Last synced at: 25 days ago - Pushed at: 9 months ago - Stars: 0 - Forks: 1

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: 1.44 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 1 - Forks: 2

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 at: about 16 hours ago - Pushed at: over 6 years ago - Stars: 6 - Forks: 0

jonathf/chaospy

Chaospy - Toolbox for performing uncertainty quantification.

Language: Python - Size: 54.4 MB - Last synced at: about 1 year ago - Pushed at: almost 2 years ago - Stars: 427 - Forks: 85

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 at: about 1 year ago - Pushed at: over 1 year 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 at: about 1 year ago - Pushed at: almost 2 years 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 at: 7 days ago - Pushed at: almost 4 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 at: over 1 year ago - Pushed at: almost 4 years ago - Stars: 1 - Forks: 0

slowbull/MPIPlatform

A platform for distributed optimization expriments using OpenMPI

Language: C++ - Size: 31.9 MB - Last synced at: over 1 year ago - Pushed at: over 7 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 at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 194 - Forks: 87

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 at: over 1 year ago - Pushed at: almost 4 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 at: over 1 year ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

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 at: over 1 year ago - Pushed at: over 4 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 at: almost 2 years ago - Pushed at: over 2 years 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 at: about 1 year ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0

hiroyuki-kasai/SimpleDeepNetToolbox

Simple MATLAB toolbox for deep learning network: Version 1.0.3

Language: Matlab - Size: 83 KB - Last synced at: about 2 years ago - Pushed at: about 6 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 at: about 2 years ago - Pushed at: about 6 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 at: about 2 years ago - Pushed at: over 2 years 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 at: almost 2 years ago - Pushed at: almost 2 years 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 at: almost 2 years ago - Pushed at: over 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 at: about 2 years ago - Pushed at: over 3 years ago - Stars: 0 - Forks: 0

variance-reduction 35 machine-learning 6 monte-carlo 6 optimization 5 stochastic-gradient-descent 5 machine-learning-algorithms 4 python 4 derivatives-pricing 4 deep-learning 4 control-variates 4 stochastic-optimization 4 pytorch 4 big-data 3 optimization-algorithms 3 simulation 3 sgd 3 antithetic-variates 3 sampling-methods 3 matlab 3 svrg 2 importance-sampling 2 numpy 2 cir-model 2 monte-carlo-simulation 2 gradient-descent 2 adagrad 2 inverse-transform-method 2 stratified-sampling 2 von-neumann 2 asian-option 2 black-scholes 2 reinforcement-learning 2 option-pricing 2 online-learning 2 forward-backward 1 relu-layer 1 sgd-momentum 1 aaai2020 1 sgd-optimizer 1 softmax-layer 1 discrete-optimization 1 variational-bayes 1 constrained-optimization 1 montecarlo-methods 1 exotic-option 1 derivatives-pricing-models 1 derivatives 1 large-scale-learning 1 replica-exchange 1 parallel-tempering 1 structure-learning 1 sghmc 1 sgmcmc 1 relax 1 r 1 rebar 1 plackett-luce-distribution 1 plackett-luce 1 permutations 1 neurips-2019 1 directed-acyclic-graph 1 adam 1 convolutional-layers 1 convolutional-neural-networks 1 deep-neural-networks 1 manifold 1 kernel-svm 1 chance-constraints 1 conic-duality 1 conic-programs 1 gas-pricing 1 natural-gas 1 uncertainty 1 deep-reinforcement-learning 1 natural-gradients 1 probability-distributions 1 variational-method 1 bayesian-neural-networks 1 hogwild 1 openmp-parallelization 1 perceptron 1 sparse-data 1 multiclass-classification 1 saga 1 softmax-regression 1 baseline 1 recurrent-neural-networks 1 non-convex-optimization 1 nonlinear-optimization 1 nonlinear-optimization-algorithms 1 riemannian-manifold 1 riemannian-optimization 1 stochastic-optimizers 1 jump-diffusion 1 pde-solver 1 pide-solver 1 sde 1 accelerated-gradient 1 data-science 1 first-order-methods 1