Nice article. We recently used t-SNE and UMAP in the field of radiation damage, for visualising the damage shapes (point defect clusters of different shapes).

Nice article. We recently used t-SNE and UMAP in the field of radiation damage, for visualising the damage shapes (point defect clusters of different shapes). The results were interesting in many ways. We found that the general layout of classes of shapes is more or less same in UMAP or t-SNE, so the global & local relationship argument didn't really work for our data. Since, the data was around 1000 points of around 50 dimensional histograms, efficiency was also not a big distinction. For us, real advantage of UMAP came out to be its amenability to work with HDBSCAN and embedding new test data. We are excited to use it on further categorising cascade and sub-cascade shapes (bigger damage areas). To check results see the following: - https://haptork.github.io/csaransh/presentation/index.html#/8/1 https://haptork.github.io/csaransh/presentation/index.html#/... : select the t-SNE or UMAP on left pane. - https://haptork.github.io/csaransh/ https://haptork.github.io/csaransh/ : Go to last pane "Cluster Classes", click on a point to see the shape on right. Select between t-SNE or UMAP on the left pane. (might take time to load) - https://arxiv.org/abs/1811.10923 https://arxiv.org/abs/1811.10923 : arXiv paper - https://github.com/haptork/csaransh https://github.com/haptork/csaransh : GitHub repo Ideas and suggestions are welcome.