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Representing Uncertainty in Property Valuation Through a Bayesian Deep Learning Approach

Open Access
|Dec 2020

References

  1. Blundell, C., Cornebise, J., Kavukcuoglu, K., & Wierstra, D. (2015). Weight uncertainty in neural networks. arXiv preprint arXiv:1505.05424.
  2. Conway, J. (2018). Artificial intelligence and machine learning: current applications in real estate. Master’s Thesis, Massachusetts Institute of Technology, Cambridge, Massachusetts
  3. French, N. (2001). Uncertainty in property valuation: The pricing of flexible leases. Journal of Corporate Real Estate, 3(1), 17–27. https://doi.org/10.1108/1463001011081145410.1108/14630010110811454
  4. French, N., & Gabrielli, L. (2004). The uncertainty of valuation. Journal of Property Investment & Finance, 22(6), 484–500. https://doi.org/10.1108/1463578041056947010.1108/14635780410569470
  5. Gal, Y., & Ghahramani, Z. (2016). Dropout as a bayesian approximation: Representing model uncertainty in deep learning. In international conference on machine learning (pp. 1050-1059).
  6. Ghahramani, Z. (2015). Probabilistic machine learning and artificial intelligence. Nature, 521(7553), 452–459. https://doi.org/10.1038/nature14541 PMID:2601744410.1038/nature14541
  7. Graves, A. (2011). Practical variational inference for neural networks. In Advances in neural information processing systems, 2348-2356.
  8. Hasenclever, L., Webb, S., Lienart, T., Vollmer, S., Lakshminarayanan, B., Blundell, C., & Teh, Y. W. (2017). Distributed Bayesian learning with stochastic natural gradient expectation propagation and the posterior server. Journal of Machine Learning Research, 18(1), 3744–3780.
  9. Harper, R., & Southern, J. (2019). A Bayesian Deep Learning Framework for End-To-End Prediction of Emotion from Heartbeat. arXiv preprint arXiv:1902.03043.
  10. Jang, H., & Lee, J. (2019). Generative Bayesian neural network model for risk-neutral pricing of American index options. Quantitative Finance, 19(4), 587–603. https://doi.org/10.1080/14697688.2018.149080710.1080/14697688.2018.1490807
  11. Johnson, A. E., Ghassemi, M. M., Nemati, S., Niehaus, K. E., Clifton, D. A., & Clifford, G. D. (2016). Machine learning and decision support in critical care. Proceedings of the IEEE. Institute of Electrical and Electronics Engineers, 104(2), 444. https://doi.org/10.1109/JPROC.2015.250197810.1109/JPROC.2015.2501978
  12. Joslin, A. (2005). An investigation into the expression of uncertainty in property valuations. Journal of Property Investment & Finance, 23(3), 269–285. https://doi.org/10.1108/1463578051059947610.1108/14635780510599476
  13. Kendall, A., & Gal, Y. (2017). What uncertainties do we need in bayesian deep learning for computer vision? In Advances in neural information processing systems, 5574-5584.
  14. Kucharska-Stasiak, E. (2013). Uncertainty of property valuation as a subject of academic research. Real Estate Management and Valuation, 21(4), 17–25. https://doi.org/10.2478/remav-2013-003310.2478/remav-2013-0033
  15. Mallinson, M., & French, N. (2000). Uncertainty in property valuation–The nature and relevance of uncertainty and how it might be measured and reported. Journal of Property Investment & Finance, 18(1), 13–32. https://doi.org/10.1108/1463578001031663610.1108/14635780010316636
  16. Meszek, W. (2007). Uncertainty phenomenon in property valuation. International Journal of Management and Decision Making, 8(5/6), 575–585. https://doi.org/10.1504/IJMDM.2007.01341910.1504/IJMDM.2007.013419
  17. Neal, R. M. (2012). Bayesian learning for neural networks (Vol. 118). Springer Science & Business Media.
  18. Seoul. (2017). Seoul Statistics. Department of housing policy.
  19. Wang, Y., & Blei, D. M. (2019). Frequentist consistency of variational Bayes. Journal of the American Statistical Association, 114(527), 1147–1161. https://doi.org/10.1080/01621459.2018.147377610.1080/01621459.2018.1473776
  20. Welling, M., & Teh, Y. W. (2011). Bayesian learning via stochastic gradient Langevin dynamics. In Proceedings of the 28th international conference on machine learning (ICML-11) (pp. 681-688).
Language: English
Page range: 15 - 23
Published on: Dec 12, 2020
Published by: Real Estate Management and Valuation
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2020 Changro Lee, Keith Key-Ho Park, published by Real Estate Management and Valuation
This work is licensed under the Creative Commons Attribution 4.0 License.