Modality-agnostic decoders leverage modality-invariant representations in human subjects' brain activity to predict stimuli irrespective of their modality (image, text, mental imagery).
A new review finds that AI is no longer being treated simply as a technical add-on for solar and wind prediction, but ...
In this conference report from ABRF 2026, the authors reflect on the meeting's insights into core facility research and ...
The models are designed to predict someone’s risk of diabetes or stroke. A few might already have been used on patients.
Using artificial-intelligence to teach other models can be cheaper and faster than building them from scratch, but this ...
Enterprise technology vendors are racing to make AI work against the structured and relational data inside databases, data ...
“QueryData shows Google is trying to create a standard way for AI agents to safely access and use data. While OpenAI focuses ...
Georgia Tech researchers have created a new AI model for decision-focused learning (DFL), called Diffusion-DFL. Recent tests ...
The advent of high-density recording technologies, such as Neuropixels and large-scale calcium imaging, has provided an unprecedented look into the ...
The ability to make adaptive decisions in uncertain environments is a fundamental characteristic of biological intelligence. Historically, computational ...
Introduction Mindfulness-based interventions are widely used, yet concerns about potential negative effects—particularly those related to mindfulness meditation practice—have gained increasing ...
Educational achievement gaps persist globally, with some ethnic minority and socioeconomically disadvantaged students consistently underperforming. Self-affirmation interventions, brief ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results