In this paper, we present a novel framework to learn sparse representations via a generalized encoder-decoder architecture. The basic idea is to adopt a fast approximation to the iterative sparse ...

We then decode the image back from sparse-codes to pixel space using a learned encoder. During inference time images may get compressed by employing both encoder & decoder. Alternatively, new images ...

The encoder, E(x), maps the input data, x, to a lower-dimensional space, z, capturing essential features. The decoder, D(z), attempts to reconstruct the original input from this compressed ...

A decoder circuit is a combinational circuit that converts a binary code into a one-hot code, where only one output is high (1) and the rest are low (0). For instance, a 2-to-4 decoder takes a 2 ...

This project is a text summarization tool built entirely from scratch using an LSTM-based encoder-decoder architecture. While it has been trained on a toy dataset and is limited in performance, it is ...

Large language models (LLMs) have changed the game for machine translation (MT). LLMs vary in architecture, ranging from decoder-only designs to encoder-decoder frameworks. Encoder-decoder models, ...

The NCTx and NCRx family of Encoders and Decoders were designed to optimize the value of established MPEG-2 infrastructure investments with a cost-effective migration to MPEG-4 and secure BCRYPT ...