16 citations · 87 across the 17 of their papers we have counts for
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cs.CV2018★ 2 cited
FINN-L: Library Extensions and Design Trade-off Analysis for Variable Precision LSTM Networks on FPGAs
Vladimir Rybalkin, Alessandro Pappalardo, Muhammad Mohsin Ghaffar +3
It is well known that many types of artificial neural networks, including recurrent networks, can achieve a high classification accuracy even with low-precision weights and activat…
cs.CV2017★ 5 cited
TensorQuant - A Simulation Toolbox for Deep Neural Network Quantization
Dominik Marek Loroch, Norbert Wehn, Franz-Josef Pfreundt +1
Recent research implies that training and inference of deep neural networks (DNN) can be computed with low precision numerical representations of the training/test data, weights an…