Kolmogorov-Arnold networks bridge AI and scientific discovery by increasing interpretability

AI has successfully been applied in many areas of science, advancing technologies like weather prediction and protein folding ...

AI uncovers double-strangeness: A new double-Lambda hypernucleus

Researchers from the High Energy Nuclear Physics Laboratory at the RIKEN Pioneering Research Institute (PRI) in Japan and ...
eLife

Human EEG and artificial neural networks reveal disentangled representations and processing timelines of object real-world size and depth in natural images

Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...
eLife

High-Fidelity Neural Speech Reconstruction through an Efficient Acoustic-Linguistic Dual-Pathway Framework

This study presents a valuable advance in reconstructing naturalistic speech from intracranial ECoG data using a dual-pathway model. The evidence supporting the claims of the authors is solid, ...
IEEE

Improving Cardiovascular Disease Prediction With Deep Learning and Correlation-Aware SMOTE

Abstract: Cardiovascular disease (CVD) ranks among the top causes of mortality globally, underscoring the urgent necessity for advanced predictive models to enhance early detection and preventative ...
EurekAlert!

New multi-modal AI framework brings human-like reasoning to self-driving vehicles

Autonomous driving systems increasingly rely on data-driven approaches, yet many still struggle with reasoning, handling rare scenarios, and transparently explaining their actions. A new study ...
IEEE

Learning-Based Motion Planning Leveraging Multivariate Deep Evidential Regression

Abstract: Learning-based motion planning methods have shown significant promise in enhancing the efficiency of traditional algorithms. However, they often face performance degradation in novel ...