Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even artificial intelligence software were all made possible. It is no wonder, then ...

This quantum output was mixed with the original image data and analyzed using a simple linear classifier. This hybrid strategy maintained information while outperforming all similarly sized machine ...

"Machine Learning in Quantum Sciences", outcome of a collaborative effort from world-leading experts, offers both an introduction to machine learning and deep neural networks, and an overview of their ...

Quantum computing exists beyond the realm of science fiction. Technology is now integrating with artificial intelligence to transform machine learning capabilities, adaptation and reasoning abilities.

Molecular machine learning (ML) underpins critical workflows in drug discovery, material science, and catalyst optimization by rapidly predicting molecular interactions and properties. For instance, ...

New hybrid quantum applications show quantum computing’s ability to optimize materials science properties using Quantum-Enhanced Generative Adversarial Networks (QGANs) and fine-tune LLM models using ...

Researchers from Tel Aviv University have developed a new method for simulating complex quantum systems that can be combined with cutting edge AI techniques The density of 6 fermions in a 2D harmonic ...

Long confined to theoretical labs and sci-fi thrillers, quantum computing is fast emerging as a real-world technology with ...

Introduction: The Portfolio Optimization Process Needs to Be Revamped. For decades, portfolio optimization has been the pinnacle of modern finance. In the 1950s, with the introduction of Harry ...