Luca Ambrogioni's repositories
GP-CaKe-project
Bayesian Effective Connectivity
CalculusTeachingMaterial
Material for teaching calculus in the Bachelor in AI at Radboud university.
Functional-GP-analysis-in-Python
A python toolbox for GP analysis written in a functional programming style
CascadingFlow
Automatic structured variational inference with cascading flows
Wasserstein-GAN-on-MNIST
This is a simple Chainer implementation of the Wasserstein GAN on MNIST digits.
NeuralEnsembleForecaster
Sample based forecasting with Kernel Mixture Networks
Brancher-1
A user-centered Python package for differentiable probabilistic inference
LocallyCoupledGP
A flexible implementation of the locally coupled GP analysis
TaylorAlgebra
A simple package for algebraic manipulation of Taylor series. It allows to sum, multiply, divide and compose Taylor series automatically.
Brancher_chainer_backend
Brancher with Chainer backend. Brancher is a python library for stochastic variational inference and differentiable probabilistic programming. This version based on chainer is functional but it is not currently maintained.
Kalman-and-Bayesian-Filters-in-Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
v130
Proceedings of AISTATS 2021