reordering RNNs
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@@ -44,7 +44,13 @@ div { text-align: justify; text-justify: inter-word; }
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2,
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None,
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'___sec0'),
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('Set up of an RNN', 2, None, '___sec1')]}
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('Set up of an RNN', 2, None, '___sec1'),
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('Solving differential equations and eigenvalue problems with '
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'RNNs',
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2,
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None,
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'___sec2'),
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('Long-Short Time Memory', 2, None, '___sec3')]}
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end of tocinfo -->
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<body>
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@@ -86,7 +92,7 @@ MathJax.Hub.Config({
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<center>[2] <b>Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University</b></center>
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<br>
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<p>
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<center><h4>Jan 8, 2019</h4></center> <!-- date -->
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<center><h4>Dec 16, 2019</h4></center> <!-- date -->
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<br>
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<p>
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<!-- !split --><br><br><br><br><br><br><br><br><br><br>
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@@ -114,6 +120,9 @@ example, they can take sentences, documents, or audio samples as
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input, making them extremely useful for natural language processing
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systems such as automatic translation and speech-to-text.
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<p>
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<b>The text here is under development</b>. Planned finished Jan 2020.
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<p>
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<!-- !split --><br><br><br><br><br><br><br><br><br><br>
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@@ -130,6 +139,25 @@ the output from the previous layer \( t-1 \), that is \( y_{t1} \).
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This means also that we need to have weights that link both the inputs \( x_t \) to the outputs \( y_t \) as well as weights that link
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the output from the previous time \( y_{t-1} \) and \( y_t \). The figure here shows an example of a simple RNN.
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<p>
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Add figures and bring up equations.
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<p>
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<!-- !split --><br><br><br><br><br><br><br><br><br><br>
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<h2 id="___sec2">Solving differential equations and eigenvalue problems with RNNs </h2>
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<p>
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Have example with eigenvalues solvers as well.
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<p>
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<!-- !split --><br><br><br><br><br><br><br><br><br><br>
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<h2 id="___sec3">Long-Short Time Memory </h2>
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<p>
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Discussions about dynamic unrolling through time. discuss memory cells, input and output
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<!-- ------------------- end of main content --------------- -->
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