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Found 3 papers, 1 papers with code
Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications
With the rapid adoption of machine learning techniques for large-scale applications in science and engineering comes the convergence of two grand challenges in visualization.
Distinguishing between Normal and Cancer Cells Using Autoencoder Node Saliency
With the trained autoencoder, we generate latent representations of a small dataset, containing pairs of normal and cancer cells of various tumor types.
Effective Quantization Approaches for Recurrent Neural Networks
These proposed approaches are evaluated on different datasets for sentiment analysis on IMDB and video frame predictions on the moving MNIST dataset.
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