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 ...

Interpretability is the science of how neural networks work internally, and how modifying their inner mechanisms can shape their behavior--e.g., adjusting a reasoning model's internal concepts to ...

Researchers from the University of Geneva (UNIGE), the Geneva University Hospitals (HUG), and the National University of Singapore (NUS) have developed a novel method for evaluating the ...

One of the major challenges facing businesses using AI is understanding exactly how these models make decisions. Traditionally, AI has been treated like a black box: Inputs go in, outputs come out, ...

OpenAI researchers are experimenting with a new approach to designing neural networks, with the aim of making AI models easier to understand, debug, and govern. Sparse models can provide enterprises ...

The AI revolution has transformed behavioral and cognitive research through unprecedented data volume, velocity, and variety (e.g., neural imaging, ...

Neel Somani has built a career that sits at the intersection of theory and practice. His work spans formal methods, mac ...

A research team from the Aerospace Information Research Institute of the Chinese Academy of Sciences (AIRCAS) has developed a ...

CNN architecture summary: The first dimension in all the layers “?” refers to the batch size. It is left as an unknown or unspecified variable within the network architecture so that it can be chosen ...