Zhaonan Wang

Orcid: 0000-0002-2613-9727

Affiliations:
  • University of Tokyo, Japan


According to our database1, Zhaonan Wang authored at least 18 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2024
Forecasting Citywide Crowd Transition Process via Convolutional Recurrent Neural Networks.
IEEE Trans. Mob. Comput., May, 2024

2023
DeepCrowd: A Deep Model for Large-Scale Citywide Crowd Density and Flow Prediction.
IEEE Trans. Knowl. Data Eng., 2023

Learning Social Meta-knowledge for Nowcasting Human Mobility in Disaster.
Proceedings of the ACM Web Conference 2023, 2023

Towards an Event-Aware Urban Mobility Prediction System.
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

MemDA: Forecasting Urban Time Series with Memory-based Drift Adaptation.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Spatio-Temporal Meta-Graph Learning for Traffic Forecasting.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Predicting Citywide Crowd Dynamics at Big Events: A Deep Learning System.
ACM Trans. Intell. Syst. Technol., 2022

DeepCrowd: A Deep Model for Large-Scale Citywide Crowd Density and Flow Prediction (Extended abstract).
Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

Yahoo! Bousai Crowd Data: A Large-Scale Crowd Density and Flow Dataset in Tokyo and Osaka.
Proceedings of the IEEE International Conference on Big Data, 2022

Event-Aware Multimodal Mobility Nowcasting.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Transfer Urban Human Mobility via POI Embedding over Multiple Cities.
Trans. Data Sci., 2021

Countrywide Origin-Destination Matrix Prediction and Its Application for COVID-19.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track, 2021

Forecasting Ambulance Demand with Profiled Human Mobility via Heterogeneous Multi-Graph Neural Networks.
Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

Spatio-Temporal-Categorical Graph Neural Networks for Fine-Grained Multi-Incident Co-Prediction.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

DL-Traff: Survey and Benchmark of Deep Learning Models for Urban Traffic Prediction.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020
CoolPath: An Application for Recommending Pedestrian Routes with Reduced Heatstroke Risk.
Proceedings of the Web and Wireless Geographical Information Systems, 2020

2019
VLUC: An Empirical Benchmark for Video-Like Urban Computing on Citywide Crowd and Traffic Prediction.
CoRR, 2019

DeepUrbanEvent: A System for Predicting Citywide Crowd Dynamics at Big Events.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019


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