As renewable power rapidly reshapes global electricity systems, engineers face a growing challenge: how to operate increasingly complex grids with ...

Mini Batch Gradient Descent is an algorithm that helps to speed up learning while dealing with a large dataset. Instead of ...

In an RL-based control system, the turbine (or wind farm) controller is realized as an agent that observes the state of the ...

Fruchter, G. (2026) Opportunism in Supply Chain Recommendations: A Dynamic Optimization Approach. Modern Economy, 17, 26-38.

Bernice Asantewaa Kyere on modeling that immediately caught my attention. The paper titled “A Critical Examination of Transformational Leadership in Implementing Flipped Classrooms for Mathematics ...

DeepSeek has introduced Manifold-Constrained Hyper-Connections (mHC), a novel architecture that stabilizes AI training and ...

Learn how to implement SGD with momentum from scratch in Python—boost your optimization skills for deep learning.

A group of tech executives, app developers and Silicon Valley philosophers is seeking to streamline the messy matters of the ...

This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...

Instagram is introducing a new tool that lets you see and control your algorithm, starting with Reels, the company announced on Wednesday. The new tool, called “Your Algorithm,” lets you view the ...

Stochastic modelling is the development of mathematical models for non-deterministic physical systems, which can adopt many possible behaviours starting from any given initial condition. Monte-Carlo ...

Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...