A new study demonstrates that deep learning models can accurately forecast drag reduction in pulsating turbulent pipe flow, even with unpredictable acceleration and deceleration patterns.
New research demonstrates that compressing computer vision models doesn’t necessarily hinder performance when faced with common image corruptions like fog or snow, and can even improve resilience.
A new deep learning approach offers improved modeling of time-dependent factors influencing survival outcomes.
New research demonstrates how machine learning applied to heart rate data from wearable devices can provide early warnings for sepsis, potentially improving outcomes.
Researchers are developing AI systems capable of not just predicting what people will do, but why they do it, by integrating emotional reasoning into world models.
A new approach leverages the power of graph neural networks to classify cognitive states directly from fMRI data.
New research reveals that large language models systematically misrepresent the diversity of public opinion on climate change, potentially skewing engagement and policy discussions.
A new benchmark reveals the significant hurdles facing artificial intelligence when it comes to complex financial reasoning with real-world documents.
Researchers have developed a hierarchical forecasting model that captures complex patterns in time series data with unprecedented accuracy and interpretability.
A new deep learning model reveals semantic connections between scientific publications and patents, offering a richer understanding of knowledge transfer.