132 citations · 146 across the 2 of their papers we have counts for
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Compressing 1D Time-Channel Separable Convolutions using Sparse Random Ternary Matrices
Gonçalo Mordido, Matthijs Van Keirsbilck, Alexander Keller
We demonstrate that 1x1-convolutions in 1D time-channel separable convolutions may be replaced by constant, sparse random ternary matrices with weights in . Such layer…
Neural Control Variates
Thomas Müller, Fabrice Rousselle, Jan Novák +1
We propose neural control variates (NCV) for unbiased variance reduction in parametric Monte Carlo integration. So far, the core challenge of applying the method of control variate…
Rethinking Full Connectivity in Recurrent Neural Networks
Matthijs Van Keirsbilck, Alexander Keller, Xiaodong Yang
Recurrent neural networks (RNNs) are omnipresent in sequence modeling tasks. Practical models usually consist of several layers of hundreds or thousands of neurons which are fully…
Instant Quantization of Neural Networks using Monte Carlo Methods
Gonçalo Mordido, Matthijs Van Keirsbilck, Alexander Keller
Low bit-width integer weights and activations are very important for efficient inference, especially with respect to lower power consumption. We propose Monte Carlo methods to quan…