
Gradient Alignment in Deep Neural Networks
One cornerstone of interpretable deep learning is the high degree of vis...
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FullJacobian Representation of Neural Networks
Nonlinear functions such as neural networks can be locally approximated...
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Knowledge Transfer with Jacobian Matching
Classical distillation methods transfer representations from a "teacher"...
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Confidence estimation in Deep Neural networks via density modelling
Stateoftheart Deep Neural Networks can be easily fooled into providin...
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Generalized Dropout
Deep Neural Networks often require good regularizers to generalize well....
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Training Sparse Neural Networks
Deep neural networks with lots of parameters are typically used for larg...
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Compensating for Large InPlane Rotations in Natural Images
Rotation invariance has been studied in the computer vision community pr...
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A Taxonomy of Deep Convolutional Neural Nets for Computer Vision
Traditional architectures for solving computer vision problems and the d...
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Learning Neural Network Architectures using Backpropagation
Deep neural networks with millions of parameters are at the heart of man...
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Datafree parameter pruning for Deep Neural Networks
Deep Neural nets (NNs) with millions of parameters are at the heart of m...
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Suraj Srinivas
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