encoder-decoder architecture
Encoder-decoder architecture refers to a neural network design where an encoder module learns to transform input data into a compact representation, and a decoder module learns to reconstruct the original input data from the encoded representation. This architecture is commonly used in tasks such as machine translation, image captioning, and speech recognition.
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