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cs.LG2026
Exploring the Trade-Off Between Structured Pruning and Fault Tolerance in Deep Neural Networks for Space Applications
Toon Vinck, Naïn Jonckers, Jaro De Roose +2
Deep Neural Networks (DNNs) inherently exhibit a degree of robustness to bit-level faults due to their distributed representation of information. As a model increases in width, thi…
cs.LG2025
Mitigating multiple single-event upsets during deep neural network inference using fault-aware training
Toon Vinck, Naïn Jonckers, Gert Dekkers +2
Deep neural networks (DNNs) are increasingly used in safety-critical applications. Reliable fault analysis and mitigation are essential to ensure their functionality in harsh envir…