This study is the first to leverage such observational data in conjunction with the power of machine learning algorithms. "Our model combines two decision tree algorithms, trained on thickness ...

the researchers identified a model that, when coupled with appropriate data augmentation and optimization partner, may help aid in the detection of skin cancer. Using an accessible deep learning ...

have developed a machine learning model that permits the prediction of bespoke Cas9 proteins that are more uniquely suited to specific targets and can be tailored with designer properties for ...

"We all used to ask, 'Why are we learning Japanese ... State School program is being presented across Queensland as a model for other schools to consider. School staff recently travelled to ...

We used a neural network to model the turbulence, and that led to better control of drones during takeoffs and landings. I’m currently working with scientists at UCSD and General Atomics on fusion ...

Get Instant Summarized Text (Gist) A self-attention neural network model enables rapid and accurate prediction of radiation shielding designs for space reactors, achieving less than 3% deviation ...

Abstract: Federated learning (FL) model marketplaces require qualified workers to collaboratively train customized models. However, recruiting optimal workers on a limited budget in non-independent ...

PrimeIntellect has released INTELLECT-2, a 32-billion parameter reasoning model post-trained using Generalized Reinforcement Policy Optimization (GRPO) within a fully decentralized, asynchronous ...