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 ...
Abstract: Graph neural networks (GNNs) witness impressive performances on homophilic graphs characterized by a higher number of edges connecting nodes of similar class labels. A decline in the ...
This is the source code repository for the Jupyter book "Physics-based Deep Learning". You can find the full, readable version online at: https ...
1️⃣ We present an interesting attempt, as illustrated in the figure below: Using the latest GPT-4o large model to generate schematic cancer gene identification. It is undeniable that the LLM possesses ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback