leowyy / mcmc-importance-sampling
Markov Chain Monte Carlo (MCMC) and importance sampling in the context of Bayesian linear regression
☆11Updated 7 years ago
Alternatives and similar repositories for mcmc-importance-sampling:
Users that are interested in mcmc-importance-sampling are comparing it to the libraries listed below
- Python code for SGMCMC for Time Series SSMs☆12Updated 4 years ago
- Learning Hawkes Processes from a Handful of Events☆13Updated last year
- RNN based on Chandler Zuo's implementation of the paper: A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction☆18Updated 9 months ago
- Experimental and exercising codes☆22Updated 6 years ago
- Adaptive MCMC and CMA-ES Python code☆14Updated 5 years ago
- Python3 project applying Gaussian process regression for forecasting stock trends☆153Updated 6 years ago
- Some codes used for the numerical examples proposed in https://arxiv.org/abs/1812.05916☆13Updated 5 years ago
- Discrete, Gaussian, and Heterogenous HMM models full implemented in Python. Missing data, Model Selection Criteria (AIC/BIC), and Semi-Su…☆77Updated last year
- Numerical solution of Hamilton Jacobi Bellman equations☆27Updated 10 years ago
- Reproducing the results of the paper "Bayesian Recurrent Neural Networks" by Fortunato et al.☆40Updated 7 years ago
- Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"☆26Updated 6 years ago
- Solving high-dimensional Partial Differential Equations with Deep Learning☆25Updated 5 years ago
- In this project I developed LSTM models for uni-variate , multivariate , multi-step time series forecasting.☆11Updated 5 years ago
- Variational Gaussian Process State-Space Models☆23Updated 9 years ago
- Implementation of the Bayesian Online Change-point Detector of Ryan Prescott Adams and David McKay.☆15Updated 3 years ago
- Bayesian neural network with Parallel Tempering MCMC for Stock Market Prediction☆39Updated 3 years ago
- Implementation of Markov Chain Monte Carlo in Python from scratch☆212Updated 4 years ago
- Bayesian Dynamic Linear Models for time-series analysis☆27Updated 3 years ago
- ☆28Updated 6 years ago
- Multi-task learning via Bayesian Neural Networks for Dynamic Time Series Prediction☆20Updated 7 years ago
- Online Change-point Detection Algorithm for Multi-Variate Data: Applications on Human/Robot Demonstrations.☆45Updated 7 years ago
- Dynamic Bayesian Network☆32Updated 12 years ago
- Bayesian Neural Network for Time Series Prediction☆15Updated 7 years ago
- Portfolio Optimization with Cumulative Prospect Theory Utility via Convex Optimization☆33Updated 11 months ago
- Tensorflow implementation of deep quantile regression☆76Updated 2 years ago
- Python package for canonical vine copula trees with mixed continuous and discrete marginals☆47Updated last year
- Library for stochastic process simulation☆14Updated last year
- Repo to supplement my tutorial on Monte Carlo Simulations and Importance Sampling☆74Updated 6 years ago
- (Work In Progress) Implementation of "Financial Time Series Prediction Using Deep Learning"☆16Updated 7 years ago
- Heterogeneous Multi-output Gaussian Processes☆52Updated 4 years ago