AI deciphers long-range DNA signals behind RNA splicing

Accurate RNA splicing is essential for gene expression and human health, yet predicting how DNA sequence variations affect ...

Cochlea network model reveals how inner ear may sort sound from noise

Over 70 million people in the U.S. are impacted by hearing loss, and age-related hearing loss is the second most common ...
The Tech Edvocate

How to create neural network

Spread the love“`html Understanding how to create a neural network can be a game-changer in the fields of artificial intelligence and machine learning. As industries increasingly rely on data-driven ...
IEEE

Understanding the Performance of Learning Precoding Policies With Graph and Convolutional Neural Networks

Abstract: Learning-based precoding has been shown able to be implemented in real-time, jointly optimized with channel acquisition, and robust to imperfect channels. Nonetheless, existing works rarely ...
IEEE

Graph Convolutional Network for Point Cloud Understanding Through Homogeneity Partitioning

Abstract: Effectively capturing complex point cloud information is essential for advanced functionalities in consumer electronics, such as augmented reality, virtual simulations, and 3D printing.
GitHub

Space-Time-Separable Graph Convolutional Network for Pose Forecasting (Accepted to ICCV '21)

Human pose forecasting is a complex structured-data sequence-modelling task, which has received increasing attention, also due to numerous potential applications. Research has mainly addressed the ...
Scientific Research Publishing

An In-Depth Analysis of Graph Neural Networks and Machine Learning Approaches for Drug Repositioning ()

1 Department of Computer Science and Engineering, Kishoreganj University, Kishoreganj, Bangladesh. 2 Department of Electrical and Computer Engineering, North South University, Dhaka, Bangladesh. 3 ...
Ars Technica

Why do LLMs make stuff up? New research peers under the hood.

One of the most frustrating things about using a large language model is dealing with its tendency to confabulate information, hallucinating answers that are not supported by its training data. From a ...