At the core of every AI coding agent is a technology called a large language model (LLM), which is a type of neural network ...
AI has successfully been applied in many areas of science, advancing technologies like weather prediction and protein folding ...
Researchers from the High Energy Nuclear Physics Laboratory at the RIKEN Pioneering Research Institute (PRI) in Japan and ...
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 ...
Wolfram-like attention framing meets spiking networks: event-triggered, energy-thrifty AI that “wakes” to stimuli.
Abstract: In this article, we propose a complementary deep-neural-network (C-DNN) processor by combining convolutional neural network (CNN) and spiking neural network (SNN) to take advantage of them.
This repository contains an implementation of a graph neural network for the segmentation and object detection in radar point clouds. As shown in the figure below, the model architecture consists of ...
Graph Neural Networks (GNNs) have become a powerful tool in order to learn from graph-structured data. Their ability to capture complex relationships and dependencies within graph structures, allows ...
This repo contains the matlab codes to reproduce the results for the paper: Vuong, Nguyen & Goulet (2024), Coupling LSTM Neural Networks and State-Space Models through Analytically Tractable Inference ...