AlejandroSantorum / scikit-rmt
Random Matrix Theory library - RMT analysis and simulation in Python
☆48Updated 11 months ago
Alternatives and similar repositories for scikit-rmt:
Users that are interested in scikit-rmt are comparing it to the libraries listed below
- esig python package☆48Updated 3 months ago
- Robust pricing and hedging via Neural SDEs☆32Updated 3 years ago
- ☆26Updated last year
- Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances☆46Updated last year
- A Brief Introduction to Path Signatures for Machine Learning Practitioners☆48Updated 3 years ago
- Signax: Signature computation in JAX☆28Updated 2 months ago
- SdePy: Numerical Integration of Ito Stochastic Differential Equations☆43Updated 3 years ago
- Deep Learning methods to solve path-dependent PDEs / to price path-dependent derivatives like exotic options☆33Updated 3 years ago
- Differentiable computations for the signature-PDE-kernel on CPU and GPU.☆53Updated 10 months ago
- Pytorch implementation of Deep Hedging, Utility Maximization and Portfolio Optimization☆13Updated 6 months ago
- Some implementations from the paper robust risk aware reinforcement learning☆35Updated 3 years ago
- Neat Bayesian machine learning examples☆55Updated 2 months ago
- Python library for Random Matrix Theory, cleaning schemes for correlation matrices, and portfolio optimization☆54Updated 2 years ago
- Toolbox for working with streaming data as rough paths in Python☆36Updated last week
- Public Implementation of Volatility Based Kernels and Moving Average Means for Accurate Forecasting with Gaussian Processes☆48Updated 2 years ago
- Covariance prediction via convex optimization☆21Updated 4 years ago
- Python package for canonical vine copula trees with mixed continuous and discrete marginals☆47Updated last year
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆102Updated last year
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 6 years ago
- Parametric estimation of multivariate Hawkes processes with general kernels.☆13Updated 10 months ago
- Python modules and jupyter notebook examples for the paper Arbitrage-free Neural-SDE Market Models.☆49Updated 2 years ago
- Python code to perform risk-sensitive Reinforcement Learning with dynamic convex risk measures☆20Updated last year
- Light-weighted code for Orthogonal Additive Gaussian Processes☆41Updated 8 months ago
- Scattering Spectra used for the analysis and generation of time-series☆33Updated 3 months ago
- Deep multistep methods to solve BSDEs of first and second order for the approximation of PDE solutions☆18Updated 4 years ago
- Finding the conditional distributions of a Gaussian Mixture Model☆12Updated 5 years ago
- PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)☆48Updated 4 years ago
- Code for "Deep Signature Transforms" (NeurIPS 2019)☆93Updated 8 months ago
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆169Updated 3 years ago
- Gaussian processes regression models with linear inequality constraints☆14Updated 8 months ago