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Realtime tSNE Visualizations with TensorFlow.js

Thursday, June 7, 2018

Posted by Nicola Pezzotti, Software Engineering Intern, Google Züricht-distributed Stochastic Neighbor EmbeddingTensorFlow Embedding ProjectorTensorBoardLinear tSNE Optimization for the WebWebGLreleasing this work as an open source libraryTensorFlow.js

Real-time evolution of the tSNE embedding for the complete MNIST dataset with our technique. The dataset contains images of 60,000 handwritten digits. You can find a live demo here.

objective functionN-body simulationBarnes-HutMNIST

Rendering of the three functions used to approximate the repulsive effect created by a single point. In the above figure the repulsive forces show a point in a blue area is pushed to the left/bottom, while a point in the red area is pushed to the right/top while a point in the white region will not move.

This animation shows the evolution of the tSNE embedding (upper left) and of the scalar fields used to approximate its gradient with normalization term (upper right), horizontal shift (bottom left) and vertical shift (bottom right).

TensorFlow.jsan open source libraryFuture WorkN-body simulationsAcknowledgementsWe would like to thank Alexander Mordvintsev, Yannick Assogba, Matt Sharifi, Anna Vilanova, Elmar Eisemann, Nikhil Thorat, Daniel Smilkov, Martin Wattenberg, Fernanda Viegas, Alessio Bazzica, Boudewijn Lelieveldt, Thomas Höllt, Baldur van Lew, Julian Thijssen and Marvin Ritter.