RAGEN stands out not just as a technical contribution but as a conceptual step toward more autonomous, reasoning-capable AI agents.

A new scientific machine learning framework developed by Professors Horacio D. Espinosa, Sridhar Krishnaswamy, and ...

MIT researchers have created a periodic table that shows how more than 20 classical machine-learning algorithms are connected ...

After uncovering a unifying algorithm that links more than 20 common machine-learning approaches, researchers organized them into a 'periodic table of machine learning' that can help scientists ...

The big challenge in deep learning is that you need a lot of data to train the neural network. Fortunately, one of my ...

A key factor preventing impact investing from reaching its maximum potential is the absence of robust monitoring and learning ...

A recent study introduces an advanced anomaly-based intrusion detection system (IDS) designed to address the increasing cyber threats targeting Internet of Things (IoT) devices. By combining machine ...

Ocean observation today is confronted with significant challenges, including limited adaptability to complex environments, low efficiency in handling ...

Based on the SO(3)-EHGNN, we further propose a molecular dynamics-powered and energy-guided deep learning framework, called Dynamics-PLI, to capture the spatial structures and energetic information ...

It also aims to increase efficiency by ensuring learners do not need to repeat learning unnecessarily. An overview of the policy is also available for learners and for managers. Policy framework for ...