Jonker-Volgenant Algorithm + t-SNE = Super Powers: https://blog.sourced.tech/post/lapjv/
#tsne #visualization
#tsne #visualization
​​Dimensionality reduction for visualizing single-cell data using UMAP
UMAP is an t-SNE replacement for #visualization.
UMAP is being increasingly accepted as a powerful tool for visualizing single cell datasets. This paper compares UMAP to #TSNE
While UMAP is unquestionably better than default t-SNE in preserving global structure, it's worth mentioning that (very recently) it was shown that this limitation of t-SNE appears to be addressable with better parameters/initialization.
Article link: https://www.nature.com/articles/nbt.4314
UMAP is an t-SNE replacement for #visualization.
UMAP is being increasingly accepted as a powerful tool for visualizing single cell datasets. This paper compares UMAP to #TSNE
While UMAP is unquestionably better than default t-SNE in preserving global structure, it's worth mentioning that (very recently) it was shown that this limitation of t-SNE appears to be addressable with better parameters/initialization.
Article link: https://www.nature.com/articles/nbt.4314
#TSNE-#CUDA implementation up to 1200x faster Sklearn
Don't waste your time, use #GPU-Accelerated t-SNE
Paper: https://arxiv.org/pdf/1807.11824.pdf
Code: https://github.com/CannyLab/tsne-cuda
Don't waste your time, use #GPU-Accelerated t-SNE
Paper: https://arxiv.org/pdf/1807.11824.pdf
Code: https://github.com/CannyLab/tsne-cuda
GitHub
GitHub - CannyLab/tsne-cuda: GPU Accelerated t-SNE for CUDA with Python bindings
GPU Accelerated t-SNE for CUDA with Python bindings - CannyLab/tsne-cuda