Closed alior101 closed 5 years ago
I have been looking forward to this for a long time! But not being a neural scientist, I don't have much clue on how to implement it. Any suggestions?
Yes. I'm working on such implementation but not in opencl. I'll share it with you once it's done and maybe you can speed it up by converting it into an opencl kernel. I'll let you know once it's ready - I'll add it as part of the examples in etaler and PR.
I'll see what I can do. May you also add some tests so I known my optimization and OpenCL implementation is correct?
sure
@alior101 FYI, If your code is relaying on my GridCell2D code. Please pull from the latest commit. I have fixed a fatal bug in the encoder. (You'll need to setup TBB for CMake for the latest commit to build properly.)
Hi Martin, Just from reading the code (sorry - I still didn't use it) I saw two issues (plz forgive me if i misunderstood your code):
No prob, just in case you are using my code and are being hit with weird problems. :smile:
My implementation is based on Numenta's paper and Matt's video. Particularly this one: https://www.youtube.com/watch?v=mP7neeymcUY
Yes, very true, but since HTM processes SDRs, I can only make cells on or off. Thus the algorithms finds the closest N cells to the bump and turn the N cells on.
Sounds interesting. I only set the scale to 0.3~1 because arbitrary values and I'm more then happy to change them, especially since the changes are based on evidences. May you elaborate more on the sunject?
implement a 2D arrays of cells featuring bumps at hex grid. Every cell can move the bump via input to its proximal dendrites. Based on continuous attractors network dynamics as in https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1000291