This important work introduces a family of interpretable Gaussian process models that allows us to learn and model sequence-function relationships in biomolecules. These models are applied to three ...

Machine learning models are increasingly applied across scientific disciplines, yet their effectiveness often hinges on heuristic decisions such as data transformations, training strategies, and model ...

1 Faculty of Land Resources Engineering, Kunming University of Science and Technology Kunming, Kunming, China 2 Pangang Group Mining Company Limited Panzhihua, Panzhihua, Sichuan, China The stability ...

Abstract: Deep reinforcement learning (DRL) has been implemented across various critical applications, including smart grids, trac management systems, and autonomous vehicles. To safeguard ...

Google appears to have disabled the &num=100 results parameter, disrupting rank trackers and prompting a rethink of desktop impressions. Many saw desktop impressions drop around Sept. 10. A working ...

The curious minds at ColdFusion showcase hyper-realistic robots that are learning at an astonishing pace. Suspect sent text saying he would 'take out' Charlie Kirk, FBI says as scrutiny of Patel's ...

1 Minutia.AI Pte. Ltd., Singapore, Singapore 2 Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milano, Italy A representation of the cause-effect mechanism is ...

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 ...

Modern large language models (LLMs) might write beautiful sonnets and elegant code, but they lack even a rudimentary ability to learn from experience. Researchers at Massachusetts Institute of ...

In my prior article for Fast Company Executive Board, I discussed how open-source AI tools are enabling businesses of every size to solve previously unsolvable business challenges without the need for ...