Codes for WWW'18 Paper-DeepMove: Predicting Human Mobility with Attentional Recurrent Network
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Updated
Jun 9, 2020 - Python
Codes for WWW'18 Paper-DeepMove: Predicting Human Mobility with Attentional Recurrent Network
Codes for paper in KDD 2020 (AI for COVID-19): Learning to Simulate Human Mobility
Codes for WWW'19 Paper-DPLink: User Identity Linkage via Deep Neural Network From Heterogeneous Mobility Data
DITRAS (DIary-based TRAjectory Simulator), a mathematical model to simulate human mobility
LSTM Mobility Model implementation using Tensorflow
This repository contains the data collected as part of the São Paulo School of Advanced Science on Smart Cities, 2017
This dataset born from the need of mobility traces provided with demographics data of the users and it allows to define several classes of users with their most relevant places. Using probability distributions, it can be used to generate slotted mobility traces for different users.
Automated Human Mobility Mode Detection Based on GPS Tracking Data
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