The Hechinger Report

Faster solutions, lower test scores: How AI is eroding math skills

Many students appear to be completing assignments faster while learning less from them. This conclusion comes from one of the largest studies of how generative AI is changing student behavior and ...
GitHub

STM-Graph: A Python Framework for Spatio-Temporal Mapping and Graph Neural Network Predictions

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...
GitHub

[AAAI 2025] DG-Mamba: Robust and Efficient Dynamic Graph Structure Learning with Selective State Space Models

This repository is the official implementation of "DG-Mamba: Robust and Efficient Dynamic Graph Structure Learning with Selective State Space Models" accepted by the Main Technical Track of the 39th ...
IEEE

A Federated Learning-Based Data Augmentation Method for Privacy Preservation Under Heterogeneous Data

Abstract: Federated learning is an important distributed machine learning paradigm. This study proposes a privacy-preserving data augmentation model for federated learning of heterogeneous data, which ...

Beyond 3-D: Data scientists introduce novel AI tool to interpret complex biological data

As humans, our eyes take in two-dimensional images that our brains convert to three-dimensional experiences. This ability enables us to be aware of our position in space, judge distances, possess ...
IEEE

Rotation- and Permutation-Equivariant Quantum Graph Neural Network for 3D Graph Data

Abstract: Equivariant quantum graph neural networks (EQGNNs) offer a potentially powerful method to process graph data. However, existing EQGNN models only consider the permutation symmetry of graphs, ...