Venu K Tangirala venuktan

## Coursera: Convolutional Neural Networks Papers.md

      
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                venuktan
                / Coursera: Convolutional Neural Networks Papers.md
            
            
              Created
              July 15, 2018 23:46
                — forked from rubychilds/Coursera: Convolutional Neural Networks Papers.md
            
          
    Classic Networks
LeNet-5: LeCun et al, "Gradient-Based Learning Applied to Document Recognition": http://yann.lecun.com/exdb/publis/pdf/lecun-01a.pdf
AlexNet: Krizhevsky et al, "ImageNet Classification with Deep Convolutional Neural Networks": https://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf
VGG-16: Simonyan et al, "Very Deep Convolutional Networks for Large-Scale Image Recognition": https://arxiv.org/pdf/1409.1556.pdf
Resnets

  
## gist:8910385
import scipy as S

def coo_submatrix_pull(matr, rows, cols):
    """
    Pulls out an arbitrary i.e. non-contiguous submatrix out of
    a sparse.coo_matrix.
    """
    if type(matr) != S.sparse.coo_matrix:
        raise TypeError('Matrix must be sparse COOrdinate format')
	import scipy as S

	def coo_submatrix_pull(matr, rows, cols):
	"""
	Pulls out an arbitrary i.e. non-contiguous submatrix out of
	a sparse.coo_matrix.
	"""
	if type(matr) != S.sparse.coo_matrix:
	raise TypeError('Matrix must be sparse COOrdinate format')