[cs702]

When I ask if this has been tested, I meant as an ANN on conventional benchmarks. Sorry if that wasn't clear.

There are a lot of ideas that are clever and seem promising... but fail to perform well on such benchmarks.

Is there a github repo with code available?

[jarekd]

Which benchmarks for multidirectional neurons? To compare with which approaches?

Multidirectional are biological neurons, but I don't know how to compare with them?

[cs702]

Can you show the world this can be made to work for, say, a toy benchmark like MNIST classification?

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To be 100% clear: My question about practical application today is orthogonal to the question about whether this research is worth pursuing!

[jarekd]

(Multidirectional) biological neural networks are no longer superior in MNIST benchmark ... but e.g. consciousness, or being able to learn from single examples.

And no, recreating it is not a task a single person can complete.

[cs702]

Alright. I've added you preprint to my reading list, so I can take a closer look at this.

[jarekd]

Just represent joint density for each neuron as a linear combination - then you can inexpensively propagate in both directions e.g. as E[X|Y,Z] or E[Y,Z|X] by substituting and normalizing ... the formulas turn out quite simple - could be hidden in dynamics of (bidirectional) biological NN ...

And for pairwise distribution becomes ~KAN, which turned out quit successful ... so we are talking about its extension: adding more possibilities, like triplewise dependencies and multidirectional propagation.