GitHub

Multimodal Emotion Recognition in Conversations via Graph Structure Learning

Python 3.10.13 PyTorch 1.13.0 torch_geometric 2.5.2 torch-cluster 1.6.1 torch-scatter 2.1.1 torch-sparse 0.6.17 torch-spline-conv 1.2.2 sparsemax 0.1.9 CUDA 11.7 Train RIGSL using the MELD dataset.
IEEE

An Adaptive Neighborhood-Resonated Graph Convolution Network for Undirected Weighted Graph Representation

Abstract: An undirected weighted graph (UWG) is the fundamental data representation in various real applications. A graph convolution network is frequently utilized for representation learning to a ...
Frontiers

Beyond single references: pangenome graphs and the future of genomic medicine

Genomic medicine relies on single reference genomes that miss crucial genetic diversity, creating diagnostic gaps that disproportionately affect underrepresented populations. Pangenome graphs, ...
IEEE

Orthogonal Fourier Analysis on Directed Acyclic Graphs via Möbius Total Variation

Abstract: Signal processing on directed acyclic graphs (DAGs) presents unique challenges. Unlike for undirected graphs, the Laplacian matrix of a DAG lacks a complete eigenbasis in general, and the ...
marktechpost

A Coding Implementation to Build an AI Agent with Live Python Execution and Automated Validation

In this tutorial, we will discover how to harness the power of an advanced AI Agent, augmented with both Python execution and result-validation capabilities, to tackle complex computational tasks. By ...
Thurrott

Build 2025: Big Updates for GitHub Copilot, Open Source Implementation in Visual Studio Code

Microsoft announced during its Build 2025 keynote that it will open source GitHub Copilot in Visual Studio Code, its lightweight, cross-platform code editor, while adding a plethora of new features to ...
GitHub

This repository contains a PyTorch implementation of the paper "Hierarchical Graph Representation Learning for the Prediction of Drug-Target Binding Affinity".

Prepare target molecular graphs, please refer to Prepare Target Molecular Graphs. python train_test_S1.py --dataset davis --cuda_id 0 --num_epochs 2000 --batch_size 512 --lr 0.0005 --model 2 ...
Scientific Research Publishing

Mora, P., Morra, G. and Yuen, D.A. (2019) A Concise Python Implementation of the Lattice Boltzmann Method on HPC for Geo-Fluid Flow. Geophysical Journal International, 220, 682 ...

ABSTRACT: The flow of electrically conducting fluids is vital in engineering applications such as Magneto-hydro-dynamic (MHD) generators, Fusion reactors, cooling systems, and Geo-physics. In this ...