Spatio-Temporal event prediction with different ml and dl algorithms.
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Updated
May 20, 2021 - Jupyter Notebook
Spatio-Temporal event prediction with different ml and dl algorithms.
An efficient and effective Bayesian calibration apporach for large-scale raw numerical model outputs
M-LibCity:基于Mindspore的城市时空预测模型开源算法库
Park. (2023). Master's Thesis. Department of Statistics. Seoul National University.
fMRI Signal Prediction with STGNN
Project - Traffic forecasting by spatio-temporal graph model
An additive dynamic model for correcting raw numerical model outputs using data from other sources, including readings collected at ground monitoring networks and weather outputs from other numerical models.
Predicting the temporal and geographical occurrence of conflicts in Myanmar with two paradigms of spatiotemporal networks.
Sample codes for training of dynamical system prediction from sparse observations using deep neural networks with Voronoi tessellation and physics constraints (DSOVT) by Wang et al.
"Biased resampling strategies for imbalanced spatio-temporal forecasting" -- DSAA 2019
FlexiCrime: A crime prediction model capable of making predictions over flexible time intervals.
Deep Spatio-Temporal Residual Networks for Mobile Location Data Prediction (instead of original Crowd Flow Prediction) - Modified ST-ResNet
Sample code for video-like crowd prediction
code repo for "Performance evaluation for forecasting modeling with spatiotemporal structures in data"
M-LibCity: An Open Source Library for Urban Spatio-temporal Prediction Models Based on MindSpore
[CIKM'2024] "EasyST: A Simple Framework for Spatio-Temporal Prediction"
[under review] Official PyTorch Implementation of "Cross-modal Autoregressive Network based on History Aggregation for Trajectory Prediction".
Using recurrent Spatio-Temporal Graph Convolutional Neural Networks to improve ETA predictions of cargo railway transportation.
This repository contains de code and instructions to train the models and prepare the datasets for the experiments in the paper "Atom: Neural Traffic Compression with Spatio-Temporal Graph Neural Networks" accepted at the 2nd ACM CONEXT GNNet 2023 Workshop.
"Evaluation procedures for forecasting with spatio-temporal data" -- ECML 2018
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