bartvanerp
commented
1 year ago Initial proposal:
- Coin toss model (Beta-Bernoulli)
- Bayesian Linear Regression
- Active Inference Mountain car
- Chance-Constrained Active Inference
- Assessing People's Skills
- Gaussian Linear Dynamical System
- Ensemble Learning of a Hidden Markov Model
- Autoregressive Model
- Hierarchical Gaussian Filter
- Bayesian ARMA model
- Infinite Data Stream
- System Identification Problem
- Univariate Gaussian Mixture Model
- Multivariate Gaussian Mixture Model
- Gamma Mixture Model
- Universal Mixtures
- Global Parameter Optimisation
- Invertible neural networks: a tutorial
- Conjugate-Computational Variational Message Passing (CVI)
- Solve GP regression by SDE
- Nonlinear Smoothing: Noisy Pendulum
- Nonlinear Smoothing: Rabbit Population
- Nonlinear Virus Spread
- Nonlinear Sensor Fusion
- Kalman filter with LSTM network driven dynamic
- Handling Missing Data
- Custom Nonlinear Node
- Probit Model (EP)
- RTS vs BIFM Smoothing
- Advanced Tutorial
Change to
Basic examples
- Modeling a coin toss (1)
- Bayesian linear regression (2)
- Hidden Markov modeling (7)
- Kalman filtering and smoothing (6, 11, 17, 26)
- Non-linear Kalman smoothing (21, 22, 23, 24, 25)
Advanced examples
- Advanced RxInfer tutorial (30)
- Nonlinear modeling with CVI (12, 19)
- Solve GP regression by SDE (20)
- Mountain car (3)
- Chance-Constrained Active Inference (4)
- Assessing People's Skills (5)
Custom nodes
- Specifying a custom node (27)
- AR Node: … (8, 10)
- GCV Node: … (9)
- Mixture Node: … (16)
- Normal Mixture node: … (13, 14)
- Gamma Mixture node: … (15)
- Flow node: … (18)
- Probit node: … (28)
- BIFM node: … (29)
albertpod
Following up on #94 and also our own observations about the documentation section, we need to restructure it. The idea is to split the example section into two (or more) subsections:
basic examplesandadvanced examples, where the latter one includes the custom and more complicated nodes that we have designed over the years.