A.I.’s First Big Math Breakthrough Is Not What It Seems

Last month, OpenAI announced that its latest version of ChatGPT had solved a major math problem, one that had stumped experts ...
IEEE

Deep Convolution Neural Network for Big Data Medical Image Classification

Abstract: Deep learning is one of the most unexpected machine learning techniques which is being used in many applications like image classification, image analysis, clinical archives and object ...
PNAS

Convolution identities for divisor sums and modular forms

Our research proves a conjecture from string theory asserting the vanishing of a specific convolution sum arising in the 4-graviton scattering amplitude in 10-dimensional type IIB string theory. The ...
IEEE

Implementing Graph Neural Networks Over Wireless Networks via Over-the-Air Computing: A Joint Communication and Computation Framework

Abstract: A Graph Neural Network (GNN) conducts the graph convolution for structured data and obtains the weighted sum over the vertices according to its graph structure. However, in the context of a ...
Frontiers

A hyperspectral image reconstruction algorithm based on RGB image using multi-scale atrous residual convolution network

Hyperspectral images are a valuable tool for remotely sensing important characteristics of a variety of landscapes, including water quality and the status of marine disasters. However, hyperspectral ...
Frontiers

Application of the Stacked Refraction Convolution Section to 2D Ocean Bottom Seismometer Wide-angle Seismic Data Along the Tamayo Through Basin, Gulf of California

The stacked refraction convolution section can be used as an interpretation tool in wide-angle refraction seismic data generated by air gun shooting and recorded by Ocean Bottom Seismometers (OBS).