BayesPiles: Visualisation Support for Bayesian Network Structure Learning
Journal Article
Vogogias, A., Kennedy, J., Archambault, D., Bach, B., Smith, V. A., & Currant, H. (2018)
BayesPiles: Visualisation Support for Bayesian Network Structure Learning. ACM transactions on intelligent systems and technology, 10(1), 1-23. https://doi.org/10.1145/3230623
We address the problem of exploring, combining and comparing large collections of scored, directed networks for understanding inferred Bayesian networks used in biology. In th...
MLCut: exploring multi-level cuts in dendrograms for biological data
Conference Proceeding
Vogogias, A., Kennedy, J., Archambault, D., Anne Smith, V., & Currant, H. (2016)
MLCut: exploring multi-level cuts in dendrograms for biological data. In C. Turkay, & T. Ruan Wan (Eds.), Computer Graphics and Visual Computing (CGVC)https://doi.org/10.2312/cgvc.20161288
Choosing a single similarity threshold for cutting dendrograms is not sufficient for performing hierarchical clustering analysis of heterogeneous data sets. In addition, alter...
Visual Encodings for Networks with Multiple Edge Types
Conference Proceeding
Vogogias, T., Archambault, D. W., Bach, B., & Kennedy, J. (2020)
Visual Encodings for Networks with Multiple Edge Types. In AVI '20: Proceedings of the International Conference on Advanced Visual Interfaces. https://doi.org/10.1145/3399715.3399827
This paper reports on a formal user study on visual encodings of networks with multiple edge types in adjacency matrices. Our tasks and conditions were inspired by real proble...