Interpretability in deep learning for finance: A case study for the Heston model

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known Heston option pricing model as a benchmark, researchers show that global ...

Research Ignited Students Publish Academic Papers and Build AI Models in Expanded PhD-Led Program

High school students gain PhD-led mentorship, publish original research, and build real-world AI models through ...

VIDEO: Think Small to Win Big - How Helikai Is Proving That Micro AI Agents Beat the Billion-Dollar Brute-Force Approach

Every CEO in the Fortune 500 has issued some version of the same mandate: We need an AI strategy. Most of them have also ...
IEEE

Quantum-Eyes: Scalable Quantum Convolutional Neural Networks for Low-Overhead Object Detection [Research Frontier]

Abstract: Quantum neural networks (QNNs) are gaining attention as a promising foundation for next-generation machine learning. However, the practical deployment of QNNs, particularly in vision tasks, ...
The Next Platform

Dassault And Nvidia Bring Industrial World Models To Physical AI

During his more than two decades with Nvidia, Rev Lebaredian has had a ringside seat to the show that has been the evolution of modern AI, from the ...
EurekAlert!

Key to human intelligence lies in how brain networks work together

Aron Barbey, the Andrew J. McKenna Family Professor of Psychology in Notre Dame’s Department of Psychology, is also the director of the Notre Dame Human Neuroimaging Center and the Decision ...
IEEE

How Many Data Does Machine Learning in Human–Computer Interaction Need?: Re-Estimating the Dataset Size for Convolutional Neural Network-Based Models of Visual Perception

Abstract: Artificial intelligence (AI)-based user-interface (UI) design and evaluation are currently constrained by the scarcity of human-generated training data. Correspondingly, choosing appropriate ...