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11/29/2017
Gaussian Process Neurons Learn Stochastic Activation Functions
We propose stochastic, non-parametric activation functions that are full...
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11/03/2017
Automatic Differentiation for Tensor Algebras
Kjolstad et. al. proposed a tensor algebra compiler. It takes expression...
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05/09/2016
Theano: A Python framework for fast computation of mathematical expressions
Theano is a Python library that allows to define, optimize, and evaluate...
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04/13/2016
A Differentiable Transition Between Additive and Multiplicative Neurons
Existing approaches to combine both additive and multiplicative neural u...
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03/19/2015
A Neural Transfer Function for a Smooth and Differentiable Transition Between Additive and Multiplicative Interactions
Existing approaches to combine both additive and multiplicative neural u...
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11/04/2013
On Fast Dropout and its Applicability to Recurrent Networks
Recurrent Neural Networks (RNNs) are rich models for the processing of s...
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01/14/2013