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Crime Prediction

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Showing 1–47 of 47 papers

TitleStatusHype
Alleviating Performance Disparity in Adversarial Spatiotemporal Graph Learning Under Zero-Inflated Distribution—0
Innovative LSGTime Model for Crime Spatiotemporal Prediction Based on MindSpore FrameworkCode0
Urban Region Representation Learning: A Flexible Approach—0
Graph Masked Autoencoder for Spatio-Temporal Graph Learning—0
Spatial-Temporal Mixture-of-Graph-Experts for Multi-Type Crime Prediction—0
SAUC: Sparsity-Aware Uncertainty Calibration for Spatiotemporal Prediction with Graph Neural NetworksCode0
Time-series Crime Prediction Across the United States Based on Socioeconomic and Political Factors—0
Uncertainty-Aware Crime Prediction With Spatial Temporal Multivariate Graph Neural Networks—0
Deep Learning Based Crime Prediction Models: Experiments and Analysis—0
Network-Based Transfer Learning Helps Improve Short-Term Crime Prediction Accuracy—0
Improving the Fairness of Deep-Learning, Short-term Crime Prediction with Under-reporting-aware Models—0
CrimeAlarm: Towards Intensive Intent Dynamics in Fine-grained Crime Prediction—0
Enhanced Urban Region Profiling with Adversarial Self-Supervised Learning for Robust Forecasting and Security—0
Spatio-Temporal Meta Contrastive LearningCode1
Explainable Spatio-Temporal Graph Neural NetworksCode1
Ranking the locations and predicting future crime occurrence by retrieving news from different Bangla online newspapers—0
Spatiotemporal and Semantic Zero-inflated Urban Anomaly Prediction—0
Crime Prediction Using Machine Learning and Deep Learning: A Systematic Review and Future Directions—0
Criminal Investigation Tracker with Suspect Prediction using Machine Learning—0
Crime Prediction using Machine Learning with a Novel Crime Dataset—0
Crime scene classification from skeletal trajectory analysis in surveillance settings—0
Spatial-Temporal Meta-path Guided Explainable Crime Prediction—0
Spatial-Temporal Hypergraph Self-Supervised Learning for Crime PredictionCode1
Multi-Graph Fusion Networks for Urban Region EmbeddingCode1
Spatial-Temporal Sequential Hypergraph Network for Crime Prediction with Dynamic Multiplex Relation LearningCode1
Are My Deep Learning Systems Fair? An Empirical Study of Fixed-Seed Training—0
Crime Prediction with Graph Neural Networks and Multivariate Normal DistributionsCode1
Multi-axis Attentive Prediction for Sparse EventData: An Application to Crime PredictionCode0
HAGEN: Homophily-Aware Graph Convolutional Recurrent Network for Crime Forecasting—0
Counterfactual Explanations Can Be Manipulated—0
AIST: An Interpretable Attention-based Deep Learning Model for Crime PredictionCode0
Crime Prediction Using Multiple-ANFIS Architecture and Spatiotemporal Data—0
Visual Analysis of Discrimination in Machine Learning—0
Analyzing the Impact of Foursquare and Streetlight Data with Human Demographics on Future Crime Prediction—0
Crime Prediction Using Spatio-Temporal Data—0
Modeling of Spatio-Temporal Hawkes Processes with Randomized Kernels—0
A Comparative Study on Crime in Denver City Based on Machine Learning and Data Mining—0
Kernel Dependence Regularizers and Gaussian Processes with Applications to Algorithmic Fairness—0
Protecting the Protected Group: Circumventing Harmful Fairness—0
Examining Deep Learning Architectures for Crime Classification and Prediction—0
Forecasting Crime with Deep Learning—0
Predicting Crime Using Spatial Features—0
Unsupervised Learning of Parsimonious General-Purpose Embeddings for User and Location Modelling—0
Crime prediction through urban metrics and statistical learning—0
Deep Learning for Real Time Crime Forecasting—0
San Francisco Crime ClassificationCode0
Crime Prediction Based On Crime Types And Using Spatial And Temporal Criminal HotspotsCode0
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