Neural networks power today’s AI boom. To understand them, all we need is a map, a cat and a few thousand dimensions.

Researchers at Rice University have developed a new machine learning (ML) algorithm that excels at interpreting the "light ...

An Institute for the Advancement of Food & Nutrition Sciences’ working group held an April meeting to come to grips with what ...

Mount Sinai researchers studying a type of heart disease known as hypertrophic cardiomyopathy (HCM) have calibrated an artificial intelligence (AI) algorithm to quickly and more specifically identify ...

Mount Sinai researchers studying a type of heart disease known as hypertrophic cardiomyopathy (HCM) have calibrated an ...

Generating clouds on these images can produce adversarial examples better aligning with human perception. In this paper, we propose an adversarial attack framework that leverages natural cloud ...

Department of Chemical and Biomolecular Engineering, University of Connecticut, Storrs, Connecticut 06269, United States Center for Clean Energy Engineering, University of Connecticut, Storrs, ...

enabling us to devise a novel classification by selecting for the most relevant TME components. Murine models were generated through hydrodynamic tail vein injection and compared with the human ...

where each search step is enhanced by Grover’s algorithm (Equation 5). The output of every Grover run, Similar to the previous subroutines, the quantum registers for these procedures are initialized ...

NOTE If the Post-Training Quantization algorithm does not meet quality requirements you can fine-tune the quantized pytorch model. You can find an example of the Quantization-Aware training pipeline ...

Heart disease classification using machine learning algorithms with hyperparameter tuning for optimized model performance. Algorithms include XGBoost, Random Forest, Logistic Regression, and moreto ...