SpatioTemporal Data

Spatiotemporal data analysis focuses on understanding patterns and trends in data that vary across both space and time, aiming to extract meaningful insights from complex, often high-dimensional datasets. Current research emphasizes the development of advanced deep learning models, including graph neural networks, transformers, and generative adversarial networks (GANs), often combined with ensemble methods and techniques like variational autoencoders (VAEs) to improve accuracy and handle missing data. These advancements are crucial for diverse applications, such as wildfire prediction, transportation optimization, and climate modeling, enabling more accurate forecasting and improved decision-making in various fields. Addressing privacy concerns through methods like differential privacy is also a significant area of focus.

Papers

November 2, 2024

ProGen: Revisiting Probabilistic Spatial-Temporal Time Series Forecasting from a Continuous Generative Perspective Using Stochastic Differential Equations
Mingze Gong, Lei Chen, Jia Li
Temporal Dependency State of the Art Forecasting Stochastic Way SpatioTemporal Data Diffusion Based Generative Probabilistic Time Series Forecasting Time sEries

October 21, 2024

Extracting Spatiotemporal Data from Gradients with Large Language Models
Lele Zheng, Yang Cao, Renhe Jiang, Kenjiro Taura, Yulong Shen, Sheng Li, Masatoshi Yoshikawa
Spatio tempOral Gradient Inversion Attack SpatioTemporal Data Gradient Attack

October 11, 2024

Encoding Agent Trajectories as Representations with Sequence Transformers
Athanasios Tsiligkaridis, Nicholas Kalinowski, Zhongheng Li, Elizabeth Hou
Language Model Transformer Megatron Decepticons Meaningful Representation Sequence of Sequence Trajectory Data SpatioTemporal Data Agent Trajectory Sequence Transformer Agent Representation

October 7, 2024

A Predictive and Optimization Approach for Enhanced Urban Mobility Using Spatiotemporal Data
Shambhavi Mishra, T. Satyanarayana Murthy
Traffic Pattern SpatioTemporal Data Traffic Congestion Urban Mobility

October 5, 2024

From Incomplete Coarse-Grained to Complete Fine-Grained: A Two-Stage Framework for Spatiotemporal Data Reconstruction
Ziyu Sun, Haoyang Su, En Wang, Funing Yang, Yongjian Yang, Wenbin Liu
Fine Grained Denoising Diffusion Probabilistic Model Two Stage Coarse Grained SpatioTemporal Data Uncertainty Induced Incomplete

September 19, 2024

Hybrid Ensemble Deep Graph Temporal Clustering for Spatiotemporal Data
Francis Ndikum Nji, Omar Faruque, Mostafa Cham, Janeja Vandana, Jianwu Wang
SpatioTemporal Data Time Series Clustering Ensemble Clustering Temporal Graph Clustering

July 20, 2024

Enhancing Wildfire Forecasting Through Multisource Spatio-Temporal Data, Deep Learning, Ensemble Models and Transfer Learning
Ayoub Jadouli, Chaker El Amrani
Deep Learning Transfer Learning Ensemble Model Temporal Data SpatioTemporal Data Wildfire Forecasting Wildfire Prediction Meteorological Satellite

July 18, 2024

A Survey on Differential Privacy for SpatioTemporal Data in Transportation Research
Rahul Bhadani
Timely Survey Differential Privacy SpatioTemporal Data User Privacy Differential Privacy Mechanism Transportation Research

June 4, 2024

ST-DPGAN: A Privacy-preserving Framework for Spatiotemporal Data Generation
Wei Shao, Rongyi Zhu, Cai Yang, Chandra Thapa, Muhammad Ejaz Ahmed, Seyit Camtepe, Rui Zhang, DuYong Kim, Hamid Menouar, Flora D. Salim
New Framework SpatioTemporal Data Spatiotemporal Datasets

May 23, 2024

CityGPT: Towards Urban IoT Learning, Analysis and Interaction with Multi-Agent System
Qinghua Guan, Jinhui Ouyang, Di Wu, Weiren Yu
General Analysis Multi Agent System Internet of Thing Interaction Generation SpatioTemporal Data Internet of Thing Data

March 19, 2024

Modal Analysis of Spatiotemporal Data via Multivariate Gaussian Process Regression
Jiwoo Song, Daning Huang
Gaussian Process Regression Dynamic Mode Decomposition SpatioTemporal Data Modal Analysis

February 25, 2024

PDETime: Rethinking Long-Term Multivariate Time Series Forecasting from the perspective of partial differential equations
Shiyi Qi, Zenglin Xu, Yiduo Li, Liangjian Wen, Qingsong Wen, Qifan Wang, Yuan Qi
Partial Differential Equation Visual Perspective Multivariate Time Series Multivariate Time Series Forecasting SpatioTemporal Data Time Index

February 23, 2024

Streaming Gaussian Dirichlet Random Fields for Spatial Predictions of High Dimensional Categorical Observations
J. E. San Soucie, H. M. Sosik, Y. Girdhar
Fast Inference SpatioTemporal Data Spatial Prediction Variational Gaussian Process

December 19, 2023

Variational Mode Decomposition-Based Nonstationary Coherent Structure Analysis for Spatiotemporal Data
Yuya Ohmichi
Non Stationary Dynamic Mode Decomposition SpatioTemporal Data Modal Analysis Variational Mode Decomposition Coherent Structure

December 4, 2023

ImputeFormer: Low Rankness-Induced Transformers for Generalizable Spatiotemporal Imputation
Tong Nie, Guoyang Qin, Wei Ma, Yuewen Mei, Jian Sun
Transformer Megatron Decepticons Low Rank Low Priority SpatioTemporal Data LOw Rank Spatiotemporal Imputation

November 24, 2023

GATGPT: A Pre-trained Large Language Model with Graph Attention Network for Spatiotemporal Imputation
Yakun Chen, Xianzhi Wang, Guandong Xu
Graph Attention Network Graph Attention Temporal Pattern SpatioTemporal Data Graph Attention Mechanism Spatiotemporal Imputation

November 4, 2023

Uncertainty Quantification of Deep Learning for Spatiotemporal Data: Challenges and Opportunities
Wenchong He, Zhe Jiang
Deep Learning Technical Challenge Uncertainty Quantification Emerging Opportunity SpatioTemporal Data Deep Learning Technology Large Scale Spatio Temporal

October 30, 2023

Deep Learning for Spatiotemporal Big Data: A Vision on Opportunities and Challenges
Zhe Jiang
Deep Learning Technical Challenge Vision Paper Emerging Opportunity Big Data SpatioTemporal Data Deep Learning Technology Earth Observation Imagery Large Scale Spatio Temporal

October 16, 2023

Temporal Embeddings: Scalable Self-Supervised Temporal Representation Learning from Spatiotemporal Data for Multimodal Computer Vision
Yi Cao, Swetava Ganguli, Vipul Pandey
Temporal Embeddings Mobility Data SpatioTemporal Data Temporal Self Multimodal Vision

September 30, 2023

SpatialRank: Urban Event Ranking with NDCG Optimization on Spatiotemporal Data
Bang An, Xun Zhou, Yongjian Zhong, Tianbao Yang
Urban Environment Temporal Correlation Spatio tempOral SpatioTemporal Data Event Forecasting

SpatioTemporal Data

Papers

ProGen: Revisiting Probabilistic Spatial-Temporal Time Series Forecasting from a Continuous Generative Perspective Using Stochastic Differential Equations

Extracting Spatiotemporal Data from Gradients with Large Language Models

Encoding Agent Trajectories as Representations with Sequence Transformers

A Predictive and Optimization Approach for Enhanced Urban Mobility Using Spatiotemporal Data

From Incomplete Coarse-Grained to Complete Fine-Grained: A Two-Stage Framework for Spatiotemporal Data Reconstruction

Hybrid Ensemble Deep Graph Temporal Clustering for Spatiotemporal Data

Enhancing Wildfire Forecasting Through Multisource Spatio-Temporal Data, Deep Learning, Ensemble Models and Transfer Learning

A Survey on Differential Privacy for SpatioTemporal Data in Transportation Research

ST-DPGAN: A Privacy-preserving Framework for Spatiotemporal Data Generation

CityGPT: Towards Urban IoT Learning, Analysis and Interaction with Multi-Agent System

Modal Analysis of Spatiotemporal Data via Multivariate Gaussian Process Regression

PDETime: Rethinking Long-Term Multivariate Time Series Forecasting from the perspective of partial differential equations

Streaming Gaussian Dirichlet Random Fields for Spatial Predictions of High Dimensional Categorical Observations

Variational Mode Decomposition-Based Nonstationary Coherent Structure Analysis for Spatiotemporal Data

ImputeFormer: Low Rankness-Induced Transformers for Generalizable Spatiotemporal Imputation

GATGPT: A Pre-trained Large Language Model with Graph Attention Network for Spatiotemporal Imputation

Uncertainty Quantification of Deep Learning for Spatiotemporal Data: Challenges and Opportunities

Deep Learning for Spatiotemporal Big Data: A Vision on Opportunities and Challenges

Temporal Embeddings: Scalable Self-Supervised Temporal Representation Learning from Spatiotemporal Data for Multimodal Computer Vision

SpatialRank: Urban Event Ranking with NDCG Optimization on Spatiotemporal Data