Publications
] , 2019. Artificial Counselor System For Stock Investment. In Innovative Applications of Artificial Intelligence (IAAI-19). 27 January . IAAI-19 Conference, Honolulu, Hawaii, USA, 2019.: AAAI Press., p. 8. Available at: https://aaai.org/ojs/index.php/AAAI/article/view/5016.
StockInvestPaper_Final.pdf, 2017. Application of Probabilistically-Weighted Graphs to Image-Based Diagnosis of Alzheimer's Disease using Diffusion MRI. In SPIE Medical Imaging Conference on Computer-Aided Diagnosis. March 3. Orlando, FL, United States: International Society for Optics and Photonics. Available at: http://dx.doi.org/10.1117/12.2254164.
, 2020. Isolation Mondrian Forest for Batch and Online Anomaly Detection. IEEE International Conference on Systems, Man, and Cybernetics (SMC) 2020. Available at: arXiv preprint arXiv:2003.03692.
imondrian.pdf, 2013. Allowing a wildfire to burn: Estimating the effect on future fire suppression costs. International Journal of Wildland Fire, 22(7), pp.871–882.
, 2012. Managing Invasive Species in a River Network. In Third International Conference on Computational Sustainability. Copenhagen, Denmark. Available at: http://www.cs.ubc.ca/ crowley/papers/compsust2012.pdf.
, Accepted. Vector Transport Free Riemannian LBFGS for Optimization on Symmetric Positive Definite Matrix Manifolds. In Asian Conference on Machine Learning (ACML). November. Virtual, p. 8. Available at: http://www.acml-conf.org/2021/conference/accepted-papers/81/.
2021-acml-godaz-vector.pdf, 2021. Generative locally linear embedding: A module for manifold unfolding and visualization. Software Impacts, 9, p.3.
2021-softimp-ghojogh-generative.pdf, 2021. Quantile–Quantile Embedding for Distribution Transformation and Manifold Embedding with Ability to Choose the Embedding Distribution. Machine Learning with Applications (MLWA), 6.
, 2021. Generative Locally Linear Embedding. Available at: https://arxiv.org/abs/2104.01525.
2021-smc-ghojogh-generative_locally_linear_embedding.pdf, 2020. Weighted Fisher Discriminant Analysisin the Input and Feature Spaces. In International Conference on Image Analysis and Recognition (ICIAR). Póvoa de Varzim, Portugal (virtual): Springer.
, 2020. Theoretical Insights into the Use of Structural Similarity Index In Generative Models and Inferential Autoencoders. In International Conference on Image Analysis and Recognition. Póvoa de Varzim, Portugal (virtual): Springer.
, 2020. Generalized Subspace Learning by Roweis Discriminant Analysis. In International Conference on Image Analysis and Recognition. Póvoa de Varzim, Portugal (virtual): Springer. Available at: http://arxiv.org/abs/1910.05437.
, 2020. Fisher Discriminant Triplet and Contrastive Losses for Training Siamese Networks. In IEEE International Joint Conference on Neural Networks (IJCNN). Glasgow, UK: IEEE.
, 2020. Backprojection for Training Feedforward Neural Networks in the Input and Feature Spaces. In International Conference on Image Analysis and Recognition. Póvoa de Varzim, Portugal (virtual): Springer.
, 2020. Anomaly Detection and Prototype Selection Using Polyhedron Curvature. In Canadian Conference on Artificial Intelligence. Ottawa, Canada: Springer, p. 10.
, 2019. Principal Component Analysis Using Structural Similarity Index for Images. In International Conference on Image Analysis and Recognition (ICIAR-19). Waterloo, Canada: Springer, Cham, pp. 77–88.
, 2019. Locally Linear Image Structural Embedding for Image Structure Manifold Learning. In International Conference on Image Analysis and Recognition (ICIAR-19). Waterloo, Canada: Springer, Cham, pp. 126–138.
, 2019. Image Structure Subspace Learning Using Structural Similarity Index. In International Conference on Image Analysis and Recognition (ICIAR-19). Waterloo, Canada: Springer, Cham, pp. 33–44.
, 2019. Fitting A Mixture Distribution to Data: Tutorial. ArXiv preprint. arXiv:1901.06708.
