A Library for Advanced Deep Time Series Models for General Time Series Analysis.

My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an attention mechanism, and entr…

CogDL: A Comprehensive Library for Graph Deep Learning (WWW 2023)

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

PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)

Modeling the health impact of gross wastewater contamination events in drinking water networks

graph wavenet

A Python package designed for the easy generation of hydraulic and water quality scenario data of water distribution networks.

Code repository for paper "Multi-scale hydraulic graph neural networks for flood modelling"

An EPANET compatible python package to simulate and analyze water distribution networks under disaster scenarios.

Battle of the Leakage Detection and Isolation Methods (BattLeDIM 2020)

Papers about explainability of GNNs

eXplainable Machine Learning 2022 at MIM UW

Applied Machine Learning Explainability Techniques, published by Packt

Interpretability and explainability of data and machine learning models

XAI - An eXplainability toolbox for machine learning

A collection of research papers and software related to explainability in graph machine learning.

A game theoretic approach to explain the output of any machine learning model.

Fit interpretable models. Explain blackbox machine learning.

An open source tool for large-scale EEG datasets processing

TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.

Machine learning models applied to water demand forecasting in the City of London.

Learning Convolutional Neural Networks with Interactive Visualization.

Think DSP: Digital Signal Processing in Python, by Allen B. Downey.

A physics-informed neural network for battery SOH estimation

Badges for your personal developer branding, profile, and projects.

A real-world dataset for EV-related research, e.g., spatiotemporal prediction and urban energy management.

ST-SSL (STSSL): Spatio-Temporal Self-Supervised Learning for Traffic Flow Forecasting/Prediction

Transformer Network for Remaining Useful Life Prediction of Lithium-Ion Batteries

Temporian is an open-source Python library for preprocessing ⚡ and feature engineering 🛠 temporal data 📈 for machine learning applications 🤖