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Lerna: Transformer Architectures for Configuring Error Correction Tools for Short- and Long-Read Genome Sequencing
We also show that the alignment rate and assembly quality computed for the corrected reads are strongly negatively correlated with the perplexity, enabling the automated selection of k-mer values for better error correction, and hence, improved assembly quality.
Federated Action Recognition on Heterogeneous Embedded Devices
Federated learning allows a large number of devices to jointly learn a model without sharing data.
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