Popular GitHub Repositories for Spectral Gnns

Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering

? A study guide to learn about Graph Neural Networks (GNNs)

List of Molecular and Material design using Generative AI and Deep Learning

[TPAMI 2024] Awesome Resources of GNNs for Time Series Analysis (GNN4TS)

A toolbox for spectral compressive imaging reconstruction including MST (CVPR 2022), CST (ECCV 2022), DAUHST (NeurIPS 2022), BiSCI (NeurIPS 2023), HDNet (CVPR 2022), MST++ (CVPRW 2022), etc.

Papers about explainability of GNNs

Python re-implementation of the (constrained) spectral clustering algorithms used in Google's speaker diarization papers.

[IJCAI 2023 survey track]A curated list of resources for chemical pre-trained models

Federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.

Experimental results obtained with the MinCutPool layer as presented in the 2020 ICML paper "Spectral Clustering with Graph Neural Networks for Graph Pooling"

The official repo for the paper "HyperSIGMA: Hyperspectral Intelligence Comprehension Foundation Model"

Tensorflow Implementation of the paper "Spectral Normalization for Generative Adversarial Networks" (ICML 2017 workshop)

pyTorch implementation of Spectral Normalization for Generative Adversarial Networks

Front-end speech processing aims at extracting proper features from short- term segments of a speech utterance, known as frames. It is a pre-requisite step toward any pattern recognition problem employing speech or audio (e.g., music). Here, we are interesting in voice disorder classification. That is, to develop two-class classifiers, which can discriminate between utterances of a subject suffering from say vocal fold paralysis and utterances of a healthy subject.The mathematical modeling of the speech production system in humans suggests that an all-pole system function is justified [1-3]. As a consequence, linear prediction coefficients (LPCs) constitute a first choice for modeling the magnitute of the short-term spectrum of speech. LPC-derived cepstral coefficients are guaranteed to discriminate between the system (e.g., vocal tract)

List of resources for mineral exploration and machine learning, generally with useful code and examples.

This repo contains the official PyTorch implementation of "Audio Super Resolution in the Spectral Domain" (ICASSP 2023)

List of molecules (small molecules, RNA, peptide, protein, enzymes, antibody, and PPIs) conformations and molecular dynamics (force fields) using generative artificial intelligence and deep learning

A2S2K-ResNet: Attention-Based Adaptive Spectral-Spatial Kernel ResNet for Hyperspectral Image Classification

[ICML 2024] A novel, efficient lightweight approach combining convolutional operations with adaptive spectral analysis as a foundation model for different time series tasks

A scalable implementation of "Learning Structural Node Embeddings Via Diffusion Wavelets (KDD 2018)".