Gumbel-Softmax Discretization Constraint, Differentiable IDS Channel, and an IDS-Correcting Code for DNA Storage

Alan J.X. Guo, Mengyi Wei, Yufan Dai, Yali Wei, Pengchen Zhang

Keywords: Gumbel-Softmax, IDS Channel, IDS-correcting Code, DNA Storage

Abstract: Insertion, deletion, and substitution (IDS) error-correcting codes have garnered increased attention with recent advancements in DNA storage technology. However, a universal method for designing IDS-correcting codes across varying channel settings remains underexplored. We present an autoencoder-based method, THEA-code, aimed at efficiently generating IDS-correcting codes for complex IDS channels. In the work, a Gumbel-Softmax discretization constraint is proposed to discretize the features of the autoencoder, and a simulated differentiable IDS channel is developed as a differentiable alternative for IDS operations. These innovations facilitate the successful convergence of the autoencoder, resulting in channel-customized IDS-correcting codes with commendable performance across complex IDS channels.

Primary Area: unsupervised, self-supervised, semi-supervised, and supervised representation learning

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Submission Number: 4142