Science

A new framework, FusAD, combines time-frequency analysis with adaptive denoising to deliver state-of-the-art performance across a broad range of time series tasks.

A new framework leverages adaptive digital twins and Bayesian learning to improve structural health monitoring and enable dynamic control under uncertain conditions.

New research reveals that state-of-the-art AI models for analyzing brain scans can unexpectedly falter when applied to new patient data, exposing a critical flaw in their learning process.

A new system proposes decoupling publication from validation, shifting the focus from acceptance rates to a data-driven measure of genuine scientific contribution.

A new deep learning framework offers a powerful approach to modeling and predicting the behavior of complex systems governed by stochastic differential equations.

As large language models grow in complexity, ensuring consistent and factual outputs requires a new approach to data refinement.

A new study demonstrates the power of machine learning and radar satellite imagery to pinpoint areas most vulnerable to flooding in the River Nyando Watershed.

A new workflow leverages artificial intelligence to simplify and accelerate complex simulations of Earth’s interior.

A new framework leverages deep reinforcement learning to autonomously manage network resources and thermal issues in critical industrial IoT deployments.

A novel machine learning framework combines clinical data and operational insights to forecast the risk of patient deterioration, empowering faster and more informed care.