Crime

  1. Newball-Ramírez D, Riascos Villegas ÁJ, Hoyos A, Dulce Rubio M (2024) A location discrete choice model of crime: Police elasticity and optimal deployment. PLoS ONE 19(3): e0294020. https://doi.org/10.1371/journal.pone.0294020
  2. Riascos Villegas ÁJ, Ñungo JS, Gómez Tobón L, Dulce Rubio M, Gómez F. Modelling underreported spatio-temporal crime events. PLoS One. 2023 Jul 12;18(7):e0287776. doi: 10.1371/journal.pone.0287776. PMID: 37437032; PMCID: PMC10337961.
  3. Isabella Rodas Arango, Mateo Dulce Rubio and Alvaro J. Riascos Villegas. 2021. A Fair Allocation Algorithm for Predictive Police Patrolling.
  4. Á. J. R. Villegas, J. S. M. Pabón, M. Dulce Rubio, S. Quintero, J. G. Vargas and H. García, “Spatio Temporal Sparsity in Homicide Prediction Models,” in IEEE Access, vol. 10, pp. 14359-14367, 2022, doi: 10.1109/ACCESS.2022.3143858.
  5. Dulce, M., Gómez, Ó., Moreno, J.S., Urcuqui, C., Villegas, Á.J.R. (2021). Interpreting a Conditional Generative Adversarial Network Model for Crime Prediction. In: Tavares, J.M.R.S., Papa, J.P., González Hidalgo, M. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2021. Lecture Notes in Computer Science(), vol 12702. Springer, Cham. https://doi.org/10.1007/978-3-030-93420-0_27
  6. Julián Chitiva Bocanegra, Douglas Newball Ramírez, Paula Rodríguez Díaz, Hamadys Benavides Gutiérrez, Mateo Dulce, and Álvaro Riascos. 2021. Visual Representations to Evaluate the Heterogeneous Effects of Urban Parks Restoration on Crime. In ACM SIGCAS Conference on Computing and Sustainable Societies (COMPASS ’21). Association for Computing Machinery, New York, NY, USA, 48–54. DOI:https://doi.org/10.1145/3460112.3471969
  7. Alvaro Riascos, Juan Moreno, Mateo Dulce, Hernan Garcia and Sebastian Quintero. 2021. Dynamic Network Analysis of Spatio-Temporal Crime Incidents. IEEE: BESC 2021 Conference Proceedings.
  8. Understanding the effect of compliance with quarantines and lockdowns on domestic violence occurrence in Bogota. Rodriguez, P., Gomez, O., Garcia, J., Riascos, A., Moreno, J., Castro, J., Panqueva, J. UNDP LAC COVID-19 Policy Documents Series 31.
  9. S. Q. Soto, J. S. M. Pabón, M. D. Rubio, A. J. Riascos and L. G. Nonato, “Graph Restrictions for Signal Processing of Homicides Data,” 2021 International Conference on Applied Artificial Intelligence (ICAPAI), 2021, pp. 1-6, doi: 10.1109/ICAPAI49758.2021.9462063.
  10. Homicide prediction using sequential features from graph signal processing. J. Moreno, S. Quintero, A. Riascos, L. Nonato and C. Sanchez. 2021. 21st Computing Conference, 2021.
  11. Self-exciting point processes with image features as covariates for robbery modeling. Dulce, M., Rodriguez, P., Moreno, J., Riascos, A., Camargo, J. Proceedings of the Computing Conference, 2021.
  12. Zero-Inflated Embeddings to Analyze Homicide Occurences Patterns. Benavides, H., Gomez O., Dulce M., Rodriguez, P., Riascos, A., and Moreno, J. 2nd International Conference on Computing and Data Science, 2021.
  13. Urcuqui, C., Moreno, J., Montenegro, C., Riascos, A., & Dulce, M. (2020, November). Accuracy and Fairness in a Conditional Generative Adversarial Model of Crime Prediction. In 2020 7th International Conference on Behavioural and Social Computing (BESC) (pp. 1-6). IEEE.
  14. A Manifold Learning Data Enrichment Methodology for Homicide Prediction. Moreno, J., Dulce, M., Riascos, A., Castano, J., and Rodriguez, P. 7th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC), 2020.