I’m new to HTM. I saw Siraj’s new video explaining how HTM works this morning. After finding some resources detailing how HTM works. It seems that HTM has trouble a dealing with dense data (HTM uses SDR).
So I wrote a special fully-connected layer that reserves dense data as input (ordinary tensors used in deep learning) and trains(and operate) itself the same way a Spatial Pooling layer in HTM does. - By comparing inputs to it’s weights and updating weights by looking at the activation state of each input.
To test if my layer works. I connected my layer to a fully-connected layer to produce a classifier(the FC layer is trained using backprpoergation). I can get my classier to classify MNIST digits correctly around 40% after traning.
Is this idea of doing HTM using dense data worth anything? Do anyone has any idea on how could I improve my design?