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 ...
eWeek

Neural Networks vs. Deep Learning

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...
Ars Technica

How a stubborn computer scientist accidentally launched the deep learning boom

During my first semester as a computer science graduate student at Princeton, I took COS 402: Artificial Intelligence. Toward the end of the semester, there was a lecture about neural networks. This ...
eLife

Adjoint propagation of error signal through modular recurrent neural networks for biologically plausible learning

Biologically plausible learning mechanisms have implications for understanding brain functions and engineering intelligent systems. Inspired by the multi-scale recurrent connectivity in the brain, we ...
Quanta Magazine

Novel Architecture Makes Neural Networks More Understandable

“Neural networks are currently the most powerful tools in artificial intelligence,” said Sebastian Wetzel, a researcher at the Perimeter Institute for Theoretical Physics. “When we scale them up to ...
Frontiers

Multi-modal Learning with Large-scale Models

Robot perception and cognition often rely on the integration of information from multiple sensory modalities, such as vision, ...
GEN

Brainoware: Organoid Neural Networks Inspire Brain-AI Hardware

“The human brain has 100 billion neurons, each neuron connected to 10,000 other neurons. Sitting on your shoulders is the most complicated object in the known universe.” — Michio Kaku, PhD. Since most ...

Generative Adversarial Networks Research Report 2026: Market to Expand by $170+ Billion by 2035 - Hyper-Personalized Advertising and Advanced Fraud Detection Dri…

The GANs market is poised for significant growth, driven by AI adoption and advancements in neural networks. Key ...
Physics World

Transfer learning could help muon tomography identify illicit nuclear materials

Muons tend to scatter more from high-atomic-number materials, so the technique is particularly sensitive to the presence of materials such as uranium. As a result, it has been used to create systems ...
Homeland Security Today

What Are Deep Neural Networks Learning About Malware?

An increasing number of modern antivirus solutions rely on machine learning (ML) techniques to protect users from malware. While ML-based approaches, like FireEye Endpoint Security’s MalwareGuard ...