Summary
- Jenkins test_hotfixes file (details)
- added a postprocess for the stochastic volatility. To be moved in the (details)
- working on figures for poster (details)
- working on last figures (details)
- improved post-process for stochastic volatility. TODO: restructure all (details)
- working on railway model (details)
- working on railway model (details)
- model to be fixed (unstable) (details)
- model unstable.... (details)
- the simpler model works (details)
- random disturbance works (details)
- redesigned model structure (details)
- refactoring the inference algorithms (details)
- working on linear filter/smoothers (details)
- working on linear Gaussian transition distributions (details)
- working on Linear filter/smoother (details)
- working on Kalman filter (details)
- setting up the INS example in order to run the Kalman filter on it... (details)
- working on linear smoother (details)
- working on linear smoother (details)
- fixing the smoothing... (details)
- linear smoother works. Figure out how to quickly get state covariances (details)
- smoothing covariances work. Now working on smoothing means (details)
- working on postprocess smoothing with different lags (details)
- fixed lag smoother works (details)
- refactored all references to old smoother/filters (details)
- working on distribution for filtering (details)
- working on railway vehicle example (details)
- working on linear filtering (details)
- fixed computation of square root for almost singular covariances in (details)
- fixed computation of square root for almost singular covariances in (details)
- working on example (details)
- working on parametric Railway model (details)
- working on linear model with hyper-parameters (details)
- working on linear models with hyper-parameters (details)
- working on ... (details)
- working on parametric distributions and transition densities (details)
- working on gradient of Kalman filter (details)
- in a maze of einsums... (details)
- working on gradients vehicle model (details)
- working on gradients for transition matrices (details)
- the gradient does not work... (details)
- working on gradients!! (details)
- added notebook py file (details)
- fixed coeff properties and working on gradient of linear filter... (details)
- Fixed the gradients (sensitivities) of the linear filter!!!! (details)
- working on parameter estimation problem (details)
- Fixes #77. Implemented function/gradient evaluation and minimization (details)
- now optimization is done with function/gradient function (details)
- working on data generation and higher dimensional cases (details)
- added fungrad option on scripts (details)
- fixing some unittest errors (details)
- this could all be wasted time.. (details)
- brancolando nel buio... (details)
- making progress??? (details)
- same change done on ConditionallyGaussianDistribution should be done on (details)
- wrapping up on railways 1d (details)
- going on with 1d (details)
- working again on gradient marginal loglikelihood (details)
- fixed marginal log likelihood!!! (details)
- fixing for tests (details)
- working on scripts for high-dimensional problem... (details)
- fixing unit tests (details)
- modified BOD example to show marginals (details)
- some updates on tutorial (details)
- working on new figs for paper with up-to-date software (details)
- fixed logging in scripts (details)
- fixed full rbf in defaults (details)
- fixed script sequential (details)
- fixed print in sequential script and fixed parallel implementation... (details)
- additional fix in sequential script (details)
- additional fix in sequential script (details)
- working on the components iterator (details)
- most of the pieces are in place. to be tested (details)
- debugging (details)
- actual implementation pass unit test_kl_minimization (details)
- it works on the tutorial examples (details)
- adding data for tutorial inv-stocvol (details)
- fixed bug in linear span kl minimization (details)
- fixed bug in parallel inverse map from samples (details)
- working on a fix for linear span solver by component (details)
- fixed all (?) bugs on the linear span from samples/ (details)
- fixed bug on linear span solve due to I19 merge (details)
- porting plots from DEPREC branch to this up-to-date branch (details)
- added btc/usd data (details)
- working on stoc vol with 10^4 data. working on tmap-max-likelihood (details)
- working on stoc vol with 10^4 data. working on tmap-max-likelihood (details)
- going on with scripts for plots (details)
- going on with scripts for plots (details)
- done with plotting routines (details)
- working on plotts (details)
- working on basic adaptivity in order to get it into the low-dim paper (details)
- working on basic adaptivity in order to get it into the low-dim paper (details)
- testing new builders (details)
- sequential inference tested with standard builder (details)
- running sequential algorithm with sequential adaptivity (details)
- improved scripts for running sequential inference (details)
- updated runner (details)
- added plot exchanges (details)
- added functionalities to tmap-sequential-tm script (details)
- started with regression adaptivityu (details)
- .... (details)
- calibrating parameters in stoc vol (details)
- finding correct configuration (details)
- working on 945 test case. Added tolerance driven adaptivity (details)
- working on script for 945 observations (details)
- working on 945 configuration and figures (details)
- ready to plot? (details)
- restructured CLI (details)
- restructuring scripts (details)
- working on trimmed postprocess (details)
- restructured CLI commands and added trimming functionalities for (details)
- updated exchange plotting (details)
- added dates in plots (details)
- added metropolis hastings and MH within Gibbs (details)
- working for figures 500 observations (details)
- fixed the default constructor, using Hermite poly for non integrated (details)
- fixed External.py import (details)
- preparing runner for slurm (details)
- setting up slurm (details)
- modified defaults integrated squared. Now using (details)
- fixing typos (details)