2. Columns correspond to outputs, and they are indexed by this three-level structure: {name of the built-in transformer {name of the individual neuron {name of the output stream ...}}}.
When one considers a particular matrix row, this correspond to "the second index, which changes when one moves along the matrix row".
Rows correspond to inputs, and they are indexed by this three-level structure: {name of the built-in transformer {name of the individual neuron {name of the input stream ...}}}.
So the matrix elements are indexed by the 6-level structure: {name of the built-in transformer of neuron-i {name of the individual neuron-i {name of the input stream {name of the built-in transformer of neuron-j {name of the individual neuron-j {name of the output stream ...}}}}}}
3 (first paragraph). I love visualizing computational graphs. It is always good to have alternative angles of view (to view the network both as a matrix and as a graph).
In some of out earlier prototypes, we did visualize how the dataflow graph of a changing network changes with time. E.g. I have this auxiliary livejournal, and its top post has the video (made in June 2015) which shows changing dataflow graph in the lower left corner: http://anhinga-drafts.livejournal.com/29929.html
This was made before we understood the matrix formalism. And I always wanted to have options to use input interfaces to edit dataflow graph directly on the graphical level (being inspired in this by some visual programming languages like Pure Data). But it's always a lot of software engineering work, and we don't have anything like this yet in our current Clojure system.
no subject
Буду отвечать кусочками...
2. Columns correspond to outputs, and they are indexed by this three-level structure: {name of the built-in transformer {name of the individual neuron {name of the output stream ...}}}.
When one considers a particular matrix row, this correspond to "the second index, which changes when one moves along the matrix row".
Rows correspond to inputs, and they are indexed by this three-level structure: {name of the built-in transformer {name of the individual neuron {name of the input stream ...}}}.
So the matrix elements are indexed by the 6-level structure: {name of the built-in transformer of neuron-i {name of the individual neuron-i {name of the input stream {name of the built-in transformer of neuron-j {name of the individual neuron-j {name of the output stream ...}}}}}}
3 (first paragraph). I love visualizing computational graphs. It is always good to have alternative angles of view (to view the network both as a matrix and as a graph).
In some of out earlier prototypes, we did visualize how the dataflow graph of a changing network
changes with time. E.g. I have this auxiliary livejournal, and its top post has the video (made in June 2015) which shows changing dataflow graph in the lower left corner: http://anhinga-drafts.livejournal.com/29929.html
This was made before we understood the matrix formalism. And I always wanted to have options to use input interfaces to edit dataflow graph directly on the graphical level (being inspired in this by some visual programming languages like Pure Data). But it's always a lot of software engineering work, and we don't have anything like this yet in our current Clojure system.