Science

This paper details an efficient approach to creating Python interfaces for complex C++ robotics libraries, unlocking their power for a wider range of applications.

This review explores how multiple species interact and organize themselves using chemical signals, revealing the complex patterns that emerge from simple rules.

A new framework enables privacy-preserving causal discovery across diverse and decentralized datasets, even when hidden variables obscure relationships.

Researchers have developed a novel deep learning framework that mimics the primate visual system to dramatically improve the detection of small, moving targets in infrared imagery.

Researchers have developed a novel method to translate the rigorous rules of Signal Temporal Logic into the flexible world of neural embeddings, enabling more efficient and scalable verification of complex systems.

A new study explores the surprisingly complex problem of moving square robots around a plane, revealing fundamental limitations even with simple maneuvers.

A new deep learning approach accurately recovers optical aberrations in smartphone cameras, enabling improved image restoration and a clearer understanding of lens characteristics.

A modular framework, SWARM-SLR AI Assistant, is presented to dramatically streamline systematic literature reviews through AI-powered guidance and an extensible tool ecosystem.

A new approach measures the alignment between how algorithms represent individuals and how those individuals represent themselves, offering a crucial check on algorithmic fairness.

Researchers have developed a novel framework that uses retrieved knowledge to construct detailed 3D representations of scenes directly from standard images.