EMBL-EBI scientists and collaborators at Heidelberg University have developed CORNETO, a new computational tool that uses ...

This paper investigates the use of probabilistic neural networks (PNNs) to model aleatoric uncertainty, which refers to the inherent variability in the input-output relationships of a system, often ...

In this research work authors have experimentally validated a blend of Machine Learning and Nonlinear Model Predictive Control (NMPC) framework designed to track the temperature profile in a Batch ...

Scientists have revealed that Convolutional Neural Networks (CNNs), a type of deep learning algorithm, demonstrate superior performance compared to conventional non-machine learning approaches when ...

In a comprehensive Genomic Press interview, Stanford University researcher Eric Sun reveals how machine learning is revolutionizing our understanding of brain aging at an unprecedented cellular ...

Machine learning helps improve accuracy and efficiency of small-molecule calculations Microsoft researchers used deep learning to create new DFT model by Sam Lemonick, special to C&EN June 20, 2025 ...

Biologically plausible synaptic plasticity rules enable recurrent neural networks to spontaneously replay sensory experiences with appropriate probabilistic structure.

High-tech classrooms are being rebranded as "learning studios" and will function more much like college lecture halls at the new Compton High School. Will the concept catch on?

Find out how this structured machine learning roadmap called I-Con could lead to breakthroughs in AI.

Machine Learning (ML) is extensively being used in order to tackle the problem of radio propagation. Besides the models that rely on tabular data, Deep Learning (DL)-based image-driven models have ...

The Advancing Innovative Methods to Promote Learning (AIM4Learning) Program is a $1.54 billion regional program funded by the International Development Association* (IDA) and International Bank for ...