A team from the Faculty of Medicine and Health Sciences and the Institute of Neurosciences at the University of Barcelona ...

Automatic Differentiation (AD) forms a cornerstone in the optimisation of machine learning models, providing an efficient computational method to obtain accurate derivatives. This technique underpins ...

In the domain of metamaterials, the push toward automated design has been accelerated by advances in generative machine learning. The advent of deep ...

Introduction: Why Data Quality Is Harder Than Ever Data quality has always been important, but in today’s world of ...

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...

Electron density prediction for a four-million-atom aluminum system using machine learning, deemed to be infeasible using traditional DFT method. × Researchers from Michigan Tech and the University of ...

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...

Machine learning can help predict whether people newly diagnosed with MS will experience disability worsening that occurs ...

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...

More aggressive feature scaling and increasingly complex transistor structures are driving a steady increase in process complexity, increasing the risk that a specified pattern may not be ...