activity
20182026
most citedautoAx: An Automatic Design Space Exploration and Circuit Building Methodology utilizing Libraries of Approximate Components

74 citations · 266 across the 40 of their papers we have counts for

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Showing 2019Show all

10 papers · 1 filter

cs.LG2019★ 1 cited

FT-ClipAct: Resilience Analysis of Deep Neural Networks and Improving their Fault Tolerance using Clipped Activation

Le-Ha Hoang, Muhammad Abdullah Hanif, Muhammad Shafique

Deep Neural Networks (DNNs) are widely being adopted for safety-critical applications, e.g., healthcare and autonomous driving. Inherently, they are considered to be highly error-t…

cs.LG2019

ReD-CaNe: A Systematic Methodology for Resilience Analysis and Design of Capsule Networks under Approximations

Alberto Marchisio, Vojtech Mrazek, Muhammad Abudllah Hanif +1

Recent advances in Capsule Networks (CapsNets) have shown their superior learning capability, compared to the traditional Convolutional Neural Networks (CNNs). However, the extreme…

cs.LG2019

FANNet: Formal Analysis of Noise Tolerance, Training Bias and Input Sensitivity in Neural Networks

Mahum Naseer, Mishal Fatima Minhas, Faiq Khalid +3

With a constant improvement in the network architectures and training methodologies, Neural Networks (NNs) are increasingly being deployed in real-world Machine Learning systems. H…

cs.NE2019

ALWANN: Automatic Layer-Wise Approximation of Deep Neural Network Accelerators without Retraining

Vojtech Mrazek, Zdenek Vasicek, Lukas Sekanina +2

The state-of-the-art approaches employ approximate computing to reduce the energy consumption of DNN hardware. Approximate DNNs then require extensive retraining afterwards to reco…

cs.LG2019

FasTrCaps: An Integrated Framework for Fast yet Accurate Training of Capsule Networks

Alberto Marchisio, Beatrice Bussolino, Alessio Colucci +4

Recently, Capsule Networks (CapsNets) have shown improved performance compared to the traditional Convolutional Neural Networks (CNNs), by encoding and preserving spatial relations…

cs.DC2019★ 74 cited

autoAx: An Automatic Design Space Exploration and Circuit Building Methodology utilizing Libraries of Approximate Components

Vojtech Mrazek, Muhammad Abdullah Hanif, Zdenek Vasicek +2

Approximate computing is an emerging paradigm for developing highly energy-efficient computing systems such as various accelerators. In the literature, many libraries of elementary…