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 ...
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, ...
Electronic Design

A Neural-Network-Based Approach to Smarter DPD Engines

An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy inefficiency in power amplifiers for next-generation wireless communication.
Security Boulevard

NDSS 2025 – Defending Against Membership Inference Attacks On Iteratively Pruned Deep Neural Network

Membership Inference Authors, Creators & Presenters: Jing Shang (Beijing Jiaotong University), Jian Wang (Beijing Jiaotong ...
The Manila Times

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
Wired

Liquid AI Is Redesigning the Neural Network

Artificial intelligence might now be solving advanced math, performing complex reasoning, and even using personal computers, but today’s algorithms could still learn a thing or two from microscopic ...

RRAM hasn't delivered yet, but stacked memory is being pitched to run neural networks in place

A team at the University of California, San Diego has redesigned how RRAM operates in an effort to accelerate the execution ...
AZoLifeSciences on MSN

New stem-cell derived platform advances study of neural network maturation

An EEG (electroencephalogram) is a painless test that uses small sensors placed on the scalp to measure the brain's electrical activity.