A new imaging-enabled knowledge graph, CardioKG, uses AI to integrate cardiac structure and function with molecular data, ...

Abstract: In this study, physics-informed graph residual learning (PhiGRL) is proposed as an effective and robust deep learning (DL)-based approach for 3-D electromagnetic (EM) modeling. Extended from ...

Our research paper has been accepted to The Web Conference 2024. . ├─ framework.png ├─ get_sub_counts.py ├─ main.py ├─ README.md │ ├─ CTAug │ ├─ evaluate.py │ ├─ model.py │ ├─ preprocess.py │ ├─ utils ...

Garmin is expanding its Connect fitness platform with a nutrition log. The feature will be integrated into the paid Connect+ ...

This is a TensorFlow implementation of Graph Convolutional Networks for the task of (semi-supervised) classification of nodes in a graph, as described in our paper: Thomas N. Kipf, Max Welling, ...

MicroCloud Hologram’s approach uses a logarithmic encoding method to reduce the number of qubits needed, representing an N-dimensional feature space using just log (N) qubits. The system forms an ...

How Time Flies is a daily feature looking back at Pantagraph archives to revisit what was happening in our community and ...

Stellar Migrator for Exchange simplifies On-Premises and Tenant-to-Tenant migrations with a secure, PowerShell-free local ...

The United States stands as the global hub of technological innovation, hosting some of the most influential Information ...

Is There a Magic Number When It Comes to Close Relationships? 1 day ...

What began with a focus on weather forecasting has evolved toward addressing errors in scientific modeling. In the collaborative environment of the Penn State Institute for Computational and Data ...