python-qinfer
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QInfer
Library for Bayesian inference via sequential Monte Carlo for quantum parameter estimation.
Hi, I am trying to modify the tutorial of simple_precession_estimation as in https://github.com/QInfer/qinfer-examples/blob/master/simple_precession_estimation.ipynb to estimate the amplitude of a Ramsey fringe. The model is set up to estimate two parameters,...
The `GaussianRandomWalkModel` derived model should invokes its underlying model for `canonicalize` since it explicitly contains different `modelparams`.
It might be worthwhile looking into doing our plots through seaborn...they have some nice stuff. [See this](https://seaborn.pydata.org/examples/pair_grid_with_kde.html) for example, which is only four lines of code.
First hyper-heuristic optimisation algorithm to be added for this pull request, an example follows: First we define a test function ```python f_rosenbrock = lambda x: numpy.sum([((x[i+1] - x[i]**2)**2 + (1...
This work in progress PR aims to produce ε-apporixmate convex hulls using the algorithm of [1603.04422](https://arxiv.org/pdf/1603.04422.pdf), with CVXOPT being used to solve the quadratic program at the innermost loop. Unfortunately,...
Sometimes the natural parameterization of your model and the parameterization that is best for sampling do not agree. There are a number of reasons this might be the case, off...
As most Qinfer developers know, myself and @ihincks have been working on extending the features and ideas of Qinfer to a more general class of probability distributions as discussed in...
A bunch of the functionality of `SMCUpdater` is not directly related to the SMC algorithm itself. For example, some methods (ex. `sample`, `est_mean()`) could be included in a new `ParticleDistribution`...
Currently the ``'loss'`` field collected by ``perf_test`` and ``perf_test_multiple`` is always taken to be the quadratic loss, but in many cases it's worthwhile to consider other loss functions (such as...