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Hi,
I'm trying to reproduce the paper, but I'm encountering a few problems. Could you assist with the following queries:
1. What command was used to initiate the training? I have the following o…
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A Hopfield network is an Ising-inspired neural network architecture used to implement associative memories. As such, it should be able to be implemented with DIMPLE in PyTorch.
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If we want to use DIMPLE to [implement Hopfield network recall](https://towardsdatascience.com/hopfield-networks-neural-memory-machines-4c94be821073), we need to be able to initialize the spins to the…
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I'm fairly new to HDC and trying to wrap my head around how it works. There's a really good example out there that shows binding with multiplication (SHAPE is CIRCLE, COLOR is RED) and bundling with a…
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Simulations built with HARK currently start with long sections of Python code setting parameters.
This custom code is written in a few different styles; it would be cleaner to have these parameters…
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Due to the publisher uploading errors, these 2 articles need to be removed. The matching process didn't work because the publisher changed the ISSN AND the titles!
Telfor Journal
Records:
All-Optical…
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`properties/hopfield_nets/softsign/w32/softsign_w32_r2_case_1_unsafe.c:5:10: fatal error: '../hopfield_nets/hop_softsign_w32_r2.h' file not found`
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and is currently disabled as a local test. need to using `running_as_notebook` and not make long animations for testing.
@dclee131
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The Hopfield network works best when states are equal to their inverse. This can be implemented by reversing states with a low-value first unit (forcing the first unit to always be the high value) and…