In a Nature Communications study, researchers from China have developed an error-aware probabilistic update (EaPU) method ...
Deep neural networks (DNNs), which power modern artificial intelligence (AI) models, are machine learning systems that learn hidden patterns from various types of data, be it images, audio or text, to ...
VFF-Net introduces three new methodologies: label-wise noise labelling (LWNL), cosine similarity-based contrastive loss (CSCL), and layer grouping (LG), addressing the challenges of applying a forward ...
EPFL researchers have developed an algorithm to train an analog neural network just as accurately as a digital one, enabling the development of more efficient alternatives to power-hungry deep ...
The hype over Large Language Models (LLMs) has reached a fever pitch. But how much of the hype is justified? We can't answer that without some straight talk - and some definitions. Time for a ...