bicv/SparseHebbianLearning
unsupervised learning of natural images -- à la SparseNet.
Jupyter NotebookNOASSERTION
Issues
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implement epochs
#38 opened by laurentperrinet - 0
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Define scope
#16 opened by laurentperrinet - 1
Show a derivation of HAP
#41 opened by laurentperrinet - 1
find another database
#13 opened by laurentperrinet - 7
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Test fast homeo
#15 opened by laurentperrinet - 0
plot SE as a function of l0
#48 opened by laurentperrinet - 4
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use precision
#39 opened by laurentperrinet - 5
1/f pink noise initialization
#9 opened by laurentperrinet - 5
implement ADAM to boost convergence
#32 opened by laurentperrinet - 0
make a comparison of learning results with different sparse coding algo
#36 opened by laurentperrinet - 2
redundant get_data function
#5 opened by laurentperrinet - 1
speed-up learning
#4 opened by laurentperrinet - 8
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do_disk
#12 opened by laurentperrinet - 1
One patches gets all the training
#11 opened by AngeloFranciosini - 0
accept 1D data
#7 opened by laurentperrinet - 2