Medicine is rapidly evolving from statistical, evidence-based approaches to predictive, genotype-directed care, driven by ...
Researchers used a process called symbolic regression to derive the equations from a biogeochemical model of the ocean.
A new airborne imaging approach can reliably detect unexploded weapons that lie in shallow coastal waters and remain an ...
Machine learning helped identify new superconductors and a process that could speed the discovery of thousands more ...
A privacy-preserving marketing framework applies homomorphic encryption to perform machine learning on encrypted ...
Alex Chen's adaptive execution framework, using reinforcement learning, cuts trading costs and improves market visibility.
Machine learning models narrow down solutions in synthesis, compounding, product design, and more.
UTokyo and Kubota develop a drone potato yield prediction method combining multispectral imagery, AI, and growth models.
Scientists have demonstrated a powerful new way to search for one of physics' biggest prizes: practical superconductors.
Principal Data Engineer Rajesh Mattaparthi is using transformer-based AI to detect hidden faults in standby power generators ...
As energy companies push AI deeper into industrial operations, success increasingly depends on governance, trusted data, and ...
MIT researchers created a technique that captures chemical arrangements across materials to improve predictions of how metal ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results