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

Research article (2021 IEEE/ACM International Conference On Computer Aided Design (ICCAD), 2021) · cited 36× · AI/ML
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ReSpawn: Energy-Efficient Fault-Tolerance for Spiking Neural Networks considering Unreliable Memories

Summary

ReSpawn: Energy-Efficient Fault-Tolerance for Spiking Neural Networks considering Unreliable Memories is a scholarly article[1].

Key Facts

  • ReSpawn: Energy-Efficient Fault-Tolerance for Spiking Neural Networks considering Unreliable Memories's instance of is recorded as scholarly article[2].

References

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). ReSpawn: Energy-Efficient Fault-Tolerance for Spiking Neural Networks considering Unreliable Memories. Retrieved May 24, 2026, from https://4ort.xyz/entity/respawn-energy-efficient-fault-tolerance-for-spiking-neural-networks-considering-unreliable-memories
MLA “ReSpawn: Energy-Efficient Fault-Tolerance for Spiking Neural Networks considering Unreliable Memories.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/respawn-energy-efficient-fault-tolerance-for-spiking-neural-networks-considering-unreliable-memories.
BibTeX @misc{4ortxyz_respawn-energy-efficient-fault-tolerance-for-spiking-neural-networks-considering-unreliable-memories_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{ReSpawn: Energy-Efficient Fault-Tolerance for Spiking Neural Networks considering Unreliable Memories}}, year = {2026}, url = {https://4ort.xyz/entity/respawn-energy-efficient-fault-tolerance-for-spiking-neural-networks-considering-unreliable-memories}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): ReSpawn: Energy-Efficient Fault-Tolerance for Spiking Neural Networks considering Unreliable Memories — https://4ort.xyz/entity/respawn-energy-efficient-fault-tolerance-for-spiking-neural-networks-considering-unreliable-memories (retrieved 2026-05-24)

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