leowyy / mcmc-importance-samplingLinks
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
Sorting:
- Collection of Monte Carlo (MC) and Markov Chain Monte Carlo (MCMC) algorithms applied on simple examples.☆386Updated 7 years ago
- Repo to supplement my tutorial on Monte Carlo Simulations and Importance Sampling☆75Updated 6 years ago
- Implementation of Markov Chain Monte Carlo in Python from scratch☆223Updated 5 years ago
- Python3 project applying Gaussian process regression for forecasting stock trends☆155Updated 7 years ago
- RNN based on Chandler Zuo's implementation of the paper: A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction☆18Updated last year
- Estimators and analysis for extreme value theory (EVT)☆22Updated 4 years ago
- A Comparison of LSTMs and Attention Mechanisms for Forecasting Financial Time Series☆72Updated 6 years ago
- Bayesian LSTM (Tensorflow)☆56Updated 2 years ago
- Financial time series forecast using dual attention RNN☆27Updated 6 years ago
- A DQN agent that optimally hedges an options portfolio.☆25Updated 5 years ago
- (Work In Progress) Implementation of "Financial Time Series Prediction Using Deep Learning"☆16Updated 8 years ago
- Optimistic Bull or Pessimistic Bear: Adaptive Deep Reinforcement Learning for Stock Portfolio Allocation☆36Updated 6 years ago
- A python tutorial for a Bayesian treatment of Linear Regression: https://zjost.github.io/bayesian-linear-regression/☆82Updated 9 years ago
- Experimental and exercising codes☆22Updated 7 years ago
- A Tensorflow Implementation of Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction☆14Updated 5 years ago
- Estimation of the Covariance Matrix - linear and nonlinear shrinkage☆23Updated 3 years ago
- Python code for SGMCMC for Time Series SSMs☆13Updated 4 years ago
- Bayesian neural network with Parallel Tempering MCMC for Stock Market Prediction☆41Updated 4 years ago
- Using Reinforcement Learning with Deep Deterministic Policy Gradient for Portfolio Optimization☆10Updated 3 years ago
- Implementation of RNN for Time Series prediction from the paper https://arxiv.org/abs/1704.02971☆59Updated 2 years ago
- Time-series analysis using restricted Boltzmann machines and dynamic Bayesian networks☆13Updated 2 years ago
- QRNN (Quantile Regression Neural Network) Keras version☆25Updated 5 years ago
- Compare how ANNs, RNNs, LSTMs, and LSTMs with attention perform on time-series analysis☆42Updated 7 years ago
- Market Risk Management with Time Series Prediction of Stock Market Trends using ARMA, ARIMA, GARCH regression models and RNN for time ser…☆22Updated 8 years ago
- Learning Hawkes Processes from a Handful of Events☆13Updated 2 years ago
- Calculate predictive causality between time series using information-theoretic techniques☆106Updated 4 years ago
- we implemented a model to predict the market price of a nonlinear chaotic time series,using reinforcement learning☆17Updated 7 years ago
- Multi-task learning via Bayesian Neural Networks for Dynamic Time Series Prediction☆21Updated 7 years ago
- ☆51Updated 7 years ago
- Bayesian Dynamic Linear Models for time-series analysis☆27Updated 3 years ago