Machine learning is a powerful tool in computational biology, enabling the analysis of a wide range of biomedical data such as genomic sequences and biological imaging. But when researchers use ...

Leaders should rethink learning strategies, embed computational thinking into decision frameworks and redesign leadership ...

In the current era of big data, the volume of information continues to grow at an unprecedented rate, giving rise to the crucial need for efficient ...

I am a computational biologist interested in interpretable machine learning for genomics and health care. Interpretable ...

We’re approaching the computational limits of deep learning. That’s according to researchers at the Massachusetts Institute of Technology, MIT-IBM Watson AI Lab, Underwood International ...

Consider a machine learning model that classifies images. If your dataset is composed of 100×100-pixel images, then your problem space has 10,000 features, one per pixel.

image: This diagram illustrates how the team reduces quantum circuit complexity in machine learning using three encoding methods—variational, genetic, and matrix product state algorithms.