Reconstructing commuters network using machine learning and urban indicators

9 August 2019

Papers citing "Reconstructing commuters network using machine learning and urban indicators"

7 / 7 papers shown

Title
Generating Origin-Destination Matrices in Neural Spatial Interaction Models Ioannis Zachos Mark Girolami Theodoros Damoulas 26 1 0 09 Oct 2024
Enhancing Global Maritime Traffic Network Forecasting with Gravity-Inspired Deep Learning Models Ruixin Song Gabriel Spadon Ronald Pelot Stan Matwin Amílcar Soares 27 4 0 23 Jan 2024
Multi-Path Long-Term Vessel Trajectories Forecasting with Probabilistic Feature Fusion for Problem Shifting Gabriel Spadon Jay Kumar Derek Eden Josh van Berkel Tom Foster Amílcar Soares Ronan Fablet Stan Matwin Ronald Pelot 42 4 0 29 Oct 2023
Using machine learning to understand causal relationships between urban form and travel CO2 emissions across continents Felix Wagner Florian Nachtigall Lukas Franken Nikola Milojevic-Dupont R. Pereira Nicolas Koch J. Runge Marta C. González F. Creutzig AI4CE 23 1 0 31 Aug 2023
Origin-Destination Network Generation via Gravity-Guided GAN Can Rong Huandong Wang Yong Li 22 5 0 06 Jun 2023
From Cities to Series: Complex Networks and Deep Learning for Improved Spatial and Temporal Analytics* Gabriel Spadon José F. Rodrigues GNN HAI 24 0 0 01 Jun 2022
Learning Geo-Contextual Embeddings for Commuting Flow Prediction Zhicheng Liu Fabio Miranda Weiting Xiong Junyan Yang Qiao Wang Claudio T. Silva AI4TS 36 70 0 04 May 2020