RonsenbergVI / MCMC-estimation-of-Stochastic-Differential-Equations-Papers
A list (quite disorganized for now) of papers tackling the Bayesian estimation of Ito processes (and their discrete time version)
☆15Updated 4 years ago
Alternatives and similar repositories for MCMC-estimation-of-Stochastic-Differential-Equations-Papers:
Users that are interested in MCMC-estimation-of-Stochastic-Differential-Equations-Papers are comparing it to the libraries listed below
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 6 years ago
- Bayesian Inference and parameter estimation in quant finance.☆43Updated 6 years ago
- Large scale simulation of ODEs or SDEs, analyze time series.☆25Updated 5 years ago
- Source code and data for the tutorial: "Getting started with particle Metropolis-Hastings for inference in nonlinear models"☆28Updated 5 years ago
- ☆18Updated 4 years ago
- Collected code and materials from the intensive course preparing for the workshop on Sequential Monte Carlo (SMC) methods at Uppsala Univ…☆21Updated 6 years ago
- Some basic algorithms for stochastic differential equations in Python/NumPy☆28Updated 11 years ago
- Markov Switching Models for Statsmodels☆22Updated 8 years ago
- Julia package for the book "Applied Quantitative Finance for Equity Derivatives"☆34Updated 2 weeks ago
- Python and MATLAB code for Stein Variational sampling methods☆24Updated 5 years ago
- Python library with C++ extensions for simulation, compensator, log-likelihood and intensity function computation for a multivariate Hawk…☆10Updated 7 years ago
- Material for the practical of the DS3 course on "Representing and comparing probabilities with kernels"☆26Updated 6 years ago
- ☆14Updated 5 years ago
- ☆77Updated 2 years ago
- Deep Learning methods to solve path-dependent PDEs / to price path-dependent derivatives like exotic options☆33Updated 3 years ago
- ☆10Updated 7 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 7 years ago
- Repository of models in Pyro☆29Updated 6 months ago
- Model Calibration with Neural Networks☆46Updated 6 years ago
- Code and examples for the project on risk-constrained Kelly gambling☆27Updated 4 years ago
- Covariance prediction via convex optimization☆19Updated 3 years ago
- "Discontinuous Hamiltonian Monte Carlo for sampling discrete parameters" by Akihiko Nishimura, David Dunson, Jianfeng Lu☆27Updated 6 years ago
- Bayesian optimisation for fast approximate inference in state-space models with intractable likelihoods☆12Updated 7 years ago
- A method to search for a subset of best performing items wrt black-box reward function☆12Updated 5 years ago
- Convex optimization over risk-neutral probabilities.☆15Updated 4 years ago
- Gaussian Process and Uncertainty Quantification Summer School 2018☆31Updated 2 years ago
- L1 Trend Filtering☆19Updated 10 months ago
- JumpDiff: Non-parametric estimator for Jump-diffusion processes for Python☆45Updated 2 years ago
- Materials for ORIE 7191: Topics in Optimization for Machine Learning☆43Updated 5 years ago
- Portfolio Construction using Stratified Models☆12Updated 3 years ago