217 citations · 1.3k across the 49 of their papers we have counts for
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cs.LG2023★ 2 cited
ISimDL: Importance Sampling-Driven Acceleration of Fault Injection Simulations for Evaluating the Robustness of Deep Learning
Alessio Colucci, Andreas Steininger, Muhammad Shafique
Deep Learning (DL) systems have proliferated in many applications, requiring specialized hardware accelerators and chips. In the nano-era, devices have become increasingly more sus…
cs.AR2023★ 1 cited
Xel-FPGAs: An End-to-End Automated Exploration Framework for Approximate Accelerators in FPGA-Based Systems
Bharath Srinivas Prabakaran, Vojtech Mrazek, Zdenek Vasicek +2
Generation and exploration of approximate circuits and accelerators has been a prominent research domain to achieve energy-efficiency and/or performance improvements. This research…