Curated fixed datasets plus sample-selection heuristics let syndrome-based neural decoders reach better error-correction performance with substantially less training data.
Radius domain-based importance sampling estimator for linear block codes over the AWGN channel,
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Doing More With Less: Towards More Data-Efficient Syndrome-Based Neural Decoders
Curated fixed datasets plus sample-selection heuristics let syndrome-based neural decoders reach better error-correction performance with substantially less training data.