IEEE

Graph Neural Network With Directional Information and Global Perception Fusion for UAV Fault Diagnosis

Abstract: Fault diagnosis is critical to flight safety for multirotor uncrewed aerial vehicles (UAVs). While graph neural networks (GNNs) have shown validity in modeling complex structural data, ...
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, ...
C&EN

A Multi-Stage Graph Neural Network–Physics-Informed Neural Network (GNN–PINN) Framework for Thermodynamic Property Prediction

Department of Chemistry and Chemical Engineering, Education and Research Center for Smart Energy and Materials, Inha University, Incheon 22212, Republic of Korea ...
GitHub

PyTorch Matrix Product Operators

This library provides PyTorch implementations of tensor-train decomposed neural network layers that can significantly reduce the number of parameters in deep neural networks while maintaining accuracy ...
GitHub

The Warmstarting model tutorial needs to be updated

. While informative, I noticed it currently lacks a motivating example and some supporting code. In my recent research, I explored warm starting by reusing a few layers from an LLM and retraining a ...
Scientific Research Publishing

Heckerman, D. (1995) A Tutorial on Learning with Bayesian Networks. Microsoft Research Technical Report.

ABSTRACT: This paper investigates the application of machine learning techniques to optimize complex spray-drying operations in manufacturing environments. Using a mixed-methods approach that combines ...