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(apologies for cross-posting)<br>
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Dear Connectionists,<br>
<br>
The estimation of information theoretical quantities is of crucial
importance in numerous problems of computational neuroscience. The
redesigned ITE (Information Theoretical Estimators) toolbox, which
obtained many new features and functionalities since its initial
release, might be of your interest in this respect. The package has
recently appeared in JMLR, a short summary of its current
capabilities:<br>
<br>
<span id="docs-internal-guid-c79a12df-9580-f75d-04eb-07a1968c6048">
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<p dir="ltr"
style="line-height:1;margin-top:0pt;margin-bottom:0pt"><span
style="font-size:15px;font-family:'Courier
New';color:rgb(0,0,0);background-color:transparent;vertical-align:baseline;white-space:pre-wrap">Information
Theoretical Estimators Toolbox</span></p>
<p dir="ltr"
style="line-height:1;margin-top:0pt;margin-bottom:0pt"><span
style="font-size:15px;font-family:'Courier
New';color:rgb(0,0,0);background-color:transparent;vertical-align:baseline;white-space:pre-wrap">Zoltán
Szabó; </span></p>
<p dir="ltr"
style="line-height:1;margin-top:0pt;margin-bottom:0pt"><span
style="font-size:15px;font-family:'Courier
New';color:rgb(0,0,0);background-color:transparent;vertical-align:baseline;white-space:pre-wrap">JMLR
15(Jan):283−287, 2014.</span></p>
<p dir="ltr"
style="line-height:1;margin-top:0pt;margin-bottom:0pt"><span
style="font-size:15px;font-family:'Courier
New';color:rgb(0,0,0);background-color:transparent;vertical-align:baseline;white-space:pre-wrap">Link:
<a href="http://jmlr.org/papers/v15/szabo14a.html">http://jmlr.org/papers/v15/szabo14a.html</a></span></p>
<br>
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<span style="font-size:15px;font-family:'Courier
New';color:rgb(0,0,0);background-color:transparent;vertical-align:baseline;white-space:pre-wrap">Abstract</span></p>
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<span style="font-size:15px;font-family:'Courier
New';color:rgb(0,0,0);background-color:transparent;vertical-align:baseline;white-space:pre-wrap">We
present ITE (information theoretical estimators) a free and
open source, multi-platform, Matlab/Octave toolbox that is
capable of estimating many different variants of entropy,
mutual information, divergence, association measures, cross
quantities, and kernels on distributions. Thanks to its highly
modular design, ITE supports additionally (i) the combinations
of the estimation techniques, (ii) the
easy construction and embedding of novel information
theoretical estimators, and (iii) their immediate application
in information theoretical optimization problems. ITE also
includes a prototype application in a central problem class of
signal processing, independent
subspace analysis and its extensions.</span></p>
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</span><br>
ITE is hosted on Bitbucket (<a class="moz-txt-link-rfc2396E" href="https://bitbucket.org/szzoli/ite/">"https://bitbucket.org/szzoli/ite/"</a>);
feel free to use it.<br>
<br>
Best, <br>
<br>
Zoltan<br>
<br>
<pre class="moz-signature" cols="72">--
Zoltan Szabo
Gatsby Computational Neuroscience Unit
University College London
<a class="moz-txt-link-freetext" href="http://www.gatsby.ucl.ac.uk/~szabo/">http://www.gatsby.ucl.ac.uk/~szabo/</a></pre>
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