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Multi-task Adversarial Spatial-Temporal Networks for Crowd Flow Prediction

https://doi.org/10.1145/3340531.3412054
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Outgoing claims: the papers this work cites, builds on, or argues with.

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Domain-Adversarial Training of Neural Networks
inferredcites →https://doi.org/10.1109/tits.2012.2200474openalex-snapshot
Learning the Dynamics of Arterial Traffic From Probe Data Using a Dynamic Bayesian Network
inferredcites →https://doi.org/10.1109/tits.2019.2900481openalex-snapshot
Deep Irregular Convolutional Residual LSTM for Urban Traffic Passenger Flows Prediction
inferredcites →https://doi.org/10.1109/tits.2019.2915525openalex-snapshot
Contextualized Spatial–Temporal Network for Taxi Origin-Destination Demand Prediction
inferredcites →https://doi.org/10.1109/tits.2019.2924971openalex-snapshot
Deep Multi-Scale Convolutional LSTM Network for Travel Demand and Origin-Destination Predictions
inferredcites →https://doi.org/10.1109/tits.2019.2955794openalex-snapshot
TrafficGAN: Network-Scale Deep Traffic Prediction With Generative Adversarial Nets
inferredcites →https://doi.org/10.1109/tkde.2019.2891537openalex-snapshot
Flow Prediction in Spatio-Temporal Networks Based on Multitask Deep Learning
inferredcites →https://doi.org/10.1109/tkde.2020.3025580openalex-snapshot
Deep Learning for Spatio-Temporal Data Mining: A Survey
inferredcites →https://doi.org/10.1145/2996913.2997016openalex-snapshot
DNN-based prediction model for spatio-temporal data
inferredcites →https://doi.org/10.1145/3057281openalex-snapshot
Computing Urban Traffic Congestions by Incorporating Sparse GPS Probe Data and Social Media Data
inferredcites →https://doi.org/10.1145/3159652.3159682openalex-snapshot
Predicting Multi-step Citywide Passenger Demands Using Attention-based Neural Networks
inferredcites →https://doi.org/10.1145/3292500.3330877openalex-snapshot
Origin-Destination Matrix Prediction via Graph Convolution
inferredcites →https://doi.org/10.1145/3378889openalex-snapshot
SeqST-GAN
inferredcites →https://doi.org/10.1177/0361198106196500103openalex-snapshot
Short-Term Traffic Flow Prediction with Regime Switching Models
inferredcites →https://doi.org/10.1609/aaai.v31i1.10735openalex-snapshot
Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction
inferredcites →https://doi.org/10.1609/aaai.v32i1.11836openalex-snapshot
Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction
inferredcites →https://doi.org/10.1609/aaai.v33i01.33015668openalex-snapshot
Revisiting Spatial-Temporal Similarity: A Deep Learning Framework for Traffic Prediction
inferredcites →https://doi.org/10.18653/v1/n16-1174openalex-snapshot
Hierarchical Attention Networks for Document Classification
inferredcites →https://doi.org/10.2307/143141openalex-snapshot
A Computer Movie Simulating Urban Growth in the Detroit Region
inferredcites →https://doi.org/10.3141/1776-25openalex-snapshot
Multivariate Vehicular Traffic Flow Prediction: Evaluation of ARIMAX Modeling
inferredcites →https://doi.org/10.48550/arxiv.1506.04214openalex-snapshot
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
inferredcites →https://doi.org/10.48550/arxiv.1812.04206openalex-snapshot
GC-LSTM: Graph Convolution Embedded LSTM for Dynamic Link Prediction

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Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Cross-Mode Knowledge Adaptation for Bike Sharing Demand Prediction Using Domain-Adversarial Graph Neural Networks
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