GitHub

A federated graph learning method to multi-party collaboration for molecular discovery

We use CUDA Version 11.7. If you have a different version of CUDA, please ensure that you install the appropriate versions of PyTorch and the CUDA toolkit that are ...
IEEE

LiP-LLM: Integrating Linear Programming and Dependency Graph With Large Language Models for Multi-Robot Task Planning

Abstract: This study proposes LiP-LLM: integrating linear programming and dependency graph with large language models (LLMs) for multi-robot task planning. For multi-robots to efficiently perform ...
Frontiers

Multi-perspective hotel operation process anomaly prediction method based on graph transformer and autoencoder

Due to the complexity of hotel operation processes, abnormal situations are inevitable, making proactive anomaly prediction essential for ensuring operational stability. Although current deep learning ...
IEEE

Graph Learning for Power Flow Analysis: A Global-Receptive Graph Iteration Network Method

Abstract: The data-driven methods based on the graph convolution architecture provide a promising direction for accelerating power flow (PF) calculation. These methods directly predict operational ...
Microsoft

Computationally Efficient Methods for Selecting Among Mixtures of Graphical Models

We describe computationally efficient methods for Bayesian model selection. The methods select among mixtures in which each component is a directed acyclic graphical model (mixtures of DAGs or MDAGs), ...