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By clauswilke
By clauswilke
t-SNE is a long-form series of generative artworks created by Claus O. Wilke in September 2021. The series consists of 99 pieces, corresponding to consecutive random seeds 1 through 99. All pieces were generated by t-distributed stochastic neighbor embedding (t-SNE), a statistical method commonly used in nonlinear dimension reduction. In all pieces, t-SNE was run multiple times on the same input data, sometimes with differing perplexity values and sometimes merely with different random seeds. The resulting point arrangements are shown either side-by-side in multiple panels or superimposed on one another in a single panel.
A private download link of the artwork as a vector graphic (pdf format) is provided via unlockable content.
t-SNE & UMAP ... They're just art—Lior Pachter
An exploration of t-distributed stochastic neighbor embedding (t-SNE) as generative mechanism. t-SNE is a widely used nonlinear dimension reduction technique. Here, however, it is used entirely for artistic purposes. The input data consists of arbitrarily generated groups of points. The groups retain their identity after t-SNE has been run, and group identity is used to color individual points in the final piece. Thus, the extent to which t-SNE retains or destroys the original group identity shapes the visual appearance of each individual piece.
The entire series was generated by a single R program, using 99 consecutive random seeds. The respective random seed is indicated in the name of each piece.
Contract Address0x495f...7b5e
Token ID
Token StandardERC-1155
ChainEthereum
MetadataCentralized
Creator Earnings
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t-SNE #16
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Seymour
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By clauswilke
By clauswilke
t-SNE is a long-form series of generative artworks created by Claus O. Wilke in September 2021. The series consists of 99 pieces, corresponding to consecutive random seeds 1 through 99. All pieces were generated by t-distributed stochastic neighbor embedding (t-SNE), a statistical method commonly used in nonlinear dimension reduction. In all pieces, t-SNE was run multiple times on the same input data, sometimes with differing perplexity values and sometimes merely with different random seeds. The resulting point arrangements are shown either side-by-side in multiple panels or superimposed on one another in a single panel.
A private download link of the artwork as a vector graphic (pdf format) is provided via unlockable content.
t-SNE & UMAP ... They're just art—Lior Pachter
An exploration of t-distributed stochastic neighbor embedding (t-SNE) as generative mechanism. t-SNE is a widely used nonlinear dimension reduction technique. Here, however, it is used entirely for artistic purposes. The input data consists of arbitrarily generated groups of points. The groups retain their identity after t-SNE has been run, and group identity is used to color individual points in the final piece. Thus, the extent to which t-SNE retains or destroys the original group identity shapes the visual appearance of each individual piece.
The entire series was generated by a single R program, using 99 consecutive random seeds. The respective random seed is indicated in the name of each piece.
Contract Address0x495f...7b5e
Token ID
Token StandardERC-1155
ChainEthereum
MetadataCentralized
Creator Earnings
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Price
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