AI uncovers double-strangeness: A new double-Lambda hypernucleus

Researchers from the High Energy Nuclear Physics Laboratory at the RIKEN Pioneering Research Institute (PRI) in Japan and ...
eLife

Human EEG and artificial neural networks reveal disentangled representations and processing timelines of object real-world size and depth in natural images

Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...
Analytics Insight

Top Java Libraries for AI and Machine Learning in 2025

Overview: In 2025, Java is expected to be a solid AI and machine-learning language.Best Java libraries for AI in 2025 can ease building neural networks, predict ...
IEEE

MVSE-Net: A Multi-View Deep Network With Semantic Embedding for LiDAR Place Recognition

Abstract: Place recognition is a critical technology in robot navigation and autonomous driving, remains challenging due to inefficient point cloud computation, limited feature representation ...
IEEE

An Enhanced Diffractive Neural Network for Metasurface Holograms With High Resolution, Low Noise, and Uniform Intensity

Abstract: In this article, an enhanced diffractive neural network is proposed for achieving metasurface holograms with high resolution, low noise, and uniform intensity. First, we prove the ...
Learn With Jay on MSN

Inside RNNs: Step-by-step word embedding process

In this video, we will look at the details of the RNN Model. We will see the mathematical equations for the RNN model, and ...
GitHub

mohansree14/Bayesian-Deep-Learning-for-Probabilistic-Financial-Forecasting

This project implements state-of-the-art deep learning models for financial time series forecasting with a focus on uncertainty quantification. The system provides not just point predictions, but ...