22 citations · 127 across the 26 of their papers we have counts for
5 papers · 1 filter
Casting Multiple Shadows: High-Dimensional Interactive Data Visualisation with Tours and Embeddings
Stuart Lee, Ursula Laa, Dianne Cook
Non-linear dimensionality reduction (NLDR) methods such as t-distributed stochastic neighbour embedding (t-SNE) are ubiquitous in the natural sciences, however, the appropriate use…
brolgar: An R package to BRowse Over Longitudinal Data Graphically and Analytically in R
Nicholas J Tierney, Dianne Cook, Tania Prvan
Longitudinal (panel) data provide the opportunity to examine temporal patterns of individuals, because measurements are collected on the same person at different, and often irregul…
Visualizing probability distributions across bivariate cyclic temporal granularities
Sayani Gupta, Rob J Hyndman, Dianne Cook +1
Deconstructing a time index into time granularities can assist in exploration and automated analysis of large temporal data sets. This paper describes classes of time deconstructio…
Burning sage: Reversing the curse of dimensionality in the visualization of high-dimensional data
Ursula Laa, Dianne Cook, Stuart Lee
In high-dimensional data analysis the curse of dimensionality reasons that points tend to be far away from the center of the distribution and on the edge of high-dimensional space.…
Hole or grain? A Section Pursuit Index for Finding Hidden Structure in Multiple Dimensions
Ursula Laa, Dianne Cook, Andreas Buja +1
Multivariate data is often visualized using linear projections, produced by techniques such as principal component analysis, linear discriminant analysis, and projection pursuit. A…