Neural networks shape many tools you rely on every day, from photo filters to medical software. Building these systems is ...

The Phi-4 model was trained on just 1.4 million carefully chosen prompt-response pairs. Instead of brute force, the Microsoft ...

Breast cancer is a highly heterogeneous malignancy among women worldwide. Traditional prognostic models relying solely on clinicopathological features offer limited predictive accuracy and lack ...

When Hurricane Melissa spun up unexpectedly in the Atlantic earlier this month, traditional forecasting models were caught off guard by its rapid intensification. Yet weather models using artificial ...

In the field of data science and engineering, tensors have become an essential tool for representing and analyzing ...

The adjusted r-squared is helpful for multiple regression and corrects for erroneous regression, giving you a more accurate correlation coefficient. If you look at the multiple regression we did, ...

Abstract: Online optimal control of quadruped robots would enable them to adapt to varying inputs and changing conditions in real time. A common way of achieving this is linear model predictive ...

Abstract: This work proposes a finite-horizon optimal control approach for set-point tracking using an Explicit Nonlinear Model Predictive Control (ENMPC) framework with integrated obstacle avoidance.