Simulation-based learning approaches this challenge differently. Rather than optimizing for knowledge transfer, simulations ...

As social media becomes the core domain of information interaction in the era of big data, the emotional information contained in the vast amount of user-generated content provides an unprecedented ...

During the acquisition of correct rejection response, rankings of functional connection separated for cortical and subcortical regions, which is predictive of the peak timing of visual information ...

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 ...

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...

Researchers at Google Cloud and UCLA have proposed a new reinforcement learning framework that significantly improves the ability of language models to learn very challenging multi-step reasoning ...

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. A few public databases provide biological activity data for ...

Seismic first break (FB) picking helps us with near surface tomography, microseismic detection among other tasks. Using image semantic segmentation (ISS) networks to do so has been a hot topic in ...

Abstract: Deep learning (DL) requires large amounts of labeled data, which is extremely time-consuming and labor-intensive to obtain for medical image segmentation ...