Introduction: Language impairments often result from severe neurological disorders, driving the development of neural prosthetics utilizing electrophysiological signals to restore comprehensible ...
Average decoding scores for modality-agnostic decoders (green), compared to modality-specific decoders trained on data from subjects viewing images (orange) or on data from subjects viewing captions ...
This study presents a useful method for the extraction of behaviour-related activity from neural population recordings based on a specific deep learning architecture, a variational autoencoder.
Our ECoG to Speech decoding framework is initially described in A Neural Speech Decoding Framework Leveraging Deep Learning and Speech Synthesis. We present a novel deep learning-based neural speech ...
A collection of practical AI engineering examples, demos, and proof-of-concepts for modern AI applications. This repository serves as a playground for experimenting with cutting-edge AI techniques and ...
Although large language models (LLMs) such as GPT-4 and LLaMA are rapidly reimagining modern-day applications, their inference is slow and difficult to optimize because it is based on autoregressive ...
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