AI for Intelligent Energy Systems Workshop is a three day workshop hosted by TU Delft DAI Lab. The workshop focuses on the applications of NLP/LLM, GNNS and RL in Energy Systems. The code labs in w…

A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.

A python library for user-friendly forecasting and anomaly detection on time series.

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

Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai

Chronos: Pretrained (Language) Models for Probabilistic Time Series Forecasting

Probabilistic time series modeling in Python

Probabilistic Gradient Boosting Machines

Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.

Multivariate Time Series Transformer, public version

A Latex template for journal review response (initially designed for IEEE TVCG)

Batching and Matching for Food Delivery in Dynamic Road Networks

A survey and paper list of current Diffusion Model for Time Series and SpatioTemporal Data with awesome resources (paper, application, review, survey, etc.).

A TensorFlow implementation of Relational Graph Attention Networks, paper: https://arxiv.org/abs/1904.05811

A Production-ready Reinforcement Learning AI Agent Library brought by the Applied Reinforcement Learning team at Meta.

An Open Source Spatio-Temporal Prediction Package

Python package built to ease deep learning on graph, on top of existing DL frameworks.

Multi-Graph Convolutional Neural Networks

Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning …

[AAAI23] This it the official github for AAAI23 paper "Spatio-Temporal Meta-Graph Learning for Traffic Forecasting"

This is the official release code of AAAI2023 accepted paper: "Spatial temporal Neural Structural Causal Models for Bike Flow Prediction"

This repository provides some of the code implemented and the data used for the work proposed in "A Cluster-Based Trip Prediction Graph Neural Network Model for Bike Sharing Systems".

Awesome Time-Series and Spatio-Temporal Related

links to conference publications in graph-based deep learning

This is the repository for the collection of Graph Neural Network for Traffic Forecasting.