Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

Neural networks have revolutionised the landscape of machine learning, yielding unprecedented performance in complex tasks ranging from image recognition to natural language processing. At the heart ...

Broad Learning Systems (BLS) have emerged as a promising alternative to conventional deep learning architectures by utilising random feature mapping and incremental learning paradigms that expand ...

The Nobel Prize in Physics was awarded to two scientists for discoveries that laid the groundwork for the artificial intelligence. British-Canadian Geoffrey Hinton, known as a 'godfather of AI', and ...

Researchers used AI and deep learning to find a link between brain structure and navigation skills but found no measurable ...

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known Heston option pricing model as a benchmark, researchers show that global ...

Researchers generated images from noise, using orders of magnitude less energy than current generative AI models require.

“Neural networks are currently the most powerful tools in artificial intelligence,” said Sebastian Wetzel, a researcher at the Perimeter Institute for Theoretical Physics. “When we scale them up to ...

An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy inefficiency in power amplifiers for next-generation wireless communication.

As artificial intelligence explodes in popularity, two of its pioneers have nabbed the 2024 Nobel Prize in physics. The prize surprised many, as these developments are typically associated with ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...