Children rapidly acquire an ability for language during early development. One theory, called iterated learning, posits that language evolves over generations to become more structured. This structure ...

This study presents an important application of high-content image-based morphological profiling to quantitatively and systematically characterize induced pluripotent stem cell-derived mixed neural ...

Machine learning is a complex discipline but implementing machine learning models is far less daunting than it used to be. Machine learning frameworks like Google’s TensorFlow ease the process of ...

InfoWorld’s 2023 Bossie Awards recognize the year’s leading open source tools for software development, data management, analytics, AI, and machine learning. When the leaves fall, the sky turns gray, ...

Back in the old days, traditional phrase-based translation systems performed their task by breaking up source sentences into multiple chunks and then translated them phrase-by-phrase. This led to ...

I came of age in the 1980s, programming personal computers such as the Commodore VIC-20 and Apple ][e at home. Going on to study computer science (CS) in college and ultimately getting a Ph.D. at ...

Neuromorphic computing algorithms based on Spiking Neural Networks (SNNs) are evolving to be a disruptive technology driving machine learning research. The overarching goal of this work is to develop ...

Institute of Electrical and Microengineering, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland Institute of Materials Science and Engineering, École Polytechnique ...

Convolutional neural networks (CNNs) have been originally used for computer vision tasks, such as image classification. While several digital soil mapping studies have been assessing these deep ...