8 citations · 8 across the 1 of their papers we have counts for
3 papers
cs.LG2019★ 8 cited
DeepCABAC: Context-adaptive binary arithmetic coding for deep neural network compression
Simon Wiedemann, Heiner Kirchhoffer, Stefan Matlage +9
We present DeepCABAC, a novel context-adaptive binary arithmetic coder for compressing deep neural networks. It quantizes each weight parameter by minimizing a weighted rate-distor…
cs.LG2019
Evaluating Recurrent Neural Network Explanations
Leila Arras, Ahmed Osman, Klaus-Robert Müller +1
Recently, several methods have been proposed to explain the predictions of recurrent neural networks (RNNs), in particular of LSTMs. The goal of these methods is to understand the…
cs.AI2018
Dual Recurrent Attention Units for Visual Question Answering
Ahmed Osman, Wojciech Samek
Visual Question Answering (VQA) requires AI models to comprehend data in two domains, vision and text. Current state-of-the-art models use learned attention mechanisms to extract r…