| Foolbox |
Foolbox is a Python toolbox to create adversarial examples that fool neural networks. Details can be found on GitHub and ReadTheDocs.
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| CircStat |
A toolbox for circular or direction statistics, containg a wide selection of descriptive techniques for such data, as well as inferential methods ranging from simple tests for uniformity to complex to factor ANOVA like tests.
It has been descriped in the paper
From the journal website, a tutorial can be downloaded as well.
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| MVD |
A toolbox to efficiently sample from (1) correlated multivariate binary random variables (multivariate Bernoulli), (2) correlated multivariate Poisson random variables and (3) correlated random variables with arbitrary marginal statistics. Applications include modeling and generating of artificial neural data. It is based on the methods in
The file also contains a tutorial to reproduce most figures from the paper.
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| NISDET |
The toolbox includes code for fitting Lp-spherically symmetric distributions as described in
It also includes code for fitting the quantitative ICA (QICA) as described in
Furthermore, it provides code for Lp-nested symmetric distributions as described in
In addition, it implements several whitening routines and allows for optimizing filter on the log-likelihood of the aforementioned models. A quick tutorial is provided explaining the usage of the toolbox.
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| Natter |
Natter - a Natural Image Statistics Toolbox for Python
- F. Sinz, J.-P. Lies, S. Gerwinn, and M. Bethge, NATTER: A Python Natural Image Statistics Toolbox, in preparation
The Natter toolbox provides a framework for model comparison of natural image statistics models and experiments with natural images in general.
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