LoicRaillon

pySIP

Stochastic state-space Inference and Prediction

feature-selection-for-machine-learning

Code repository for the online course Feature Selection for Machine Learning

From-thermal-network-to-SSM

Convert thermal network to state-space model

gaussianize

Transforms univariate data into normally distributed data

hamiltonian-monte-carlo

Python implementations of Hamiltonian Monte Carlo samplers

kalman-jax

Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX

PRBS

Pseudo Random Binary Signal

pymc3

Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano

pySIP

Stochastic state-space Inference and Prediction

Thesis

LoicRaillon/From-thermal-network-to-SSM

Convert thermal network to state-space model

LoicRaillon/Thesis

LoicRaillon/feature-selection-for-machine-learning

Code repository for the online course Feature Selection for Machine Learning

LoicRaillon/gaussianize

Transforms univariate data into normally distributed data

LoicRaillon/hamiltonian-monte-carlo

Python implementations of Hamiltonian Monte Carlo samplers

LoicRaillon/kalman-jax

Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX

LoicRaillon/PRBS

Pseudo Random Binary Signal

LoicRaillon/pymc3

Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano

LoicRaillon/pySIP

Stochastic state-space Inference and Prediction

LoicRaillon/sampyl

MCMC samplers for Bayesian estimation in Python, including Metropolis-Hastings, NUTS, and Slice

LoicRaillon/skforecast

Time series forecasting with scikit-learn models