ReSpawn: Energy-Efficient Fault-Tolerance for Spiking Neural Networks considering Unreliable Memories

23 August 2021

Papers citing "ReSpawn: Energy-Efficient Fault-Tolerance for Spiking Neural Networks considering Unreliable Memories"

8 / 8 papers shown

Title
Enabling Efficient Processing of Spiking Neural Networks with On-Chip Learning on Commodity Neuromorphic Processors for Edge AI Systems Rachmad Vidya Wicaksana Putra Pasindu Wickramasinghe Muhammad Shafique 48 0 0 01 Apr 2025
EnforceSNN: Enabling Resilient and Energy-Efficient Spiking Neural Network Inference considering Approximate DRAMs for Embedded Systems Rachmad Vidya Wicaksana Putra Muhammad Abdullah Hanif Muhammad Shafique 24 11 0 08 Apr 2023
TopSpark: A Timestep Optimization Methodology for Energy-Efficient Spiking Neural Networks on Autonomous Mobile Agents Rachmad Vidya Wicaksana Putra Muhammad Shafique 37 12 0 03 Mar 2023
Improving Reliability of Spiking Neural Networks through Fault Aware Threshold Voltage Optimization Ayesha Siddique K. A. Hoque 19 5 0 12 Jan 2023
Mantis: Enabling Energy-Efficient Autonomous Mobile Agents with Spiking Neural Networks Rachmad Vidya Wicaksana Putra Muhammad Shafique 37 6 0 24 Dec 2022
enpheeph: A Fault Injection Framework for Spiking and Compressed Deep Neural Networks Alessio Colucci A. Steininger Muhammad Shafique 19 12 0 31 Jul 2022
SoftSNN: Low-Cost Fault Tolerance for Spiking Neural Network Accelerators under Soft Errors Rachmad Vidya Wicaksana Putra Muhammad Abdullah Hanif Muhammad Shafique 23 28 0 10 Mar 2022
Robust Machine Learning Systems: Challenges, Current Trends, Perspectives, and the Road Ahead Muhammad Shafique Mahum Naseer T. Theocharides C. Kyrkou O. Mutlu Lois Orosa Jungwook Choi OOD 75 100 0 04 Jan 2021