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Nesterov momentum and gradient normalization to improve t-SNE convergence and neighborhood preservation, without early exaggeration.

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Semantic segmentation of computed tomography for radiotherapy with deep learning: compensating insufficient annotation quality using contour augmentation., , и . Medical Imaging: Image Processing, том 10949 из SPIE Proceedings, стр. 109492P. SPIE, (2019)Perplexity-free Parametric t-SNE., , , , и . ESANN, стр. 387-392. (2020)Stochastic quartet approach for fast multidimensional scaling., , , и . ESANN, (2021)Multi-organ Segmentation of Chest CT Images in Radiation Oncology: Comparison of Standard and Dilated UNet., , и . ACIVS, том 11182 из Lecture Notes in Computer Science, стр. 188-199. Springer, (2018)Tutorial - Machine Learning and Information Theoretic Methods for Molecular Biology and Medicine., , , и . ESANN, (2022)On the number of latent representations in deep neural networks for tabular data., , , , и . ESANN, (2023)Single-pass uncertainty estimation with layer ensembling for regression: application to proton therapy dose prediction for head and neck cancer., , , и . ESANN, (2023)PyBIDS: Python tools for BIDS datasets., , , , , , , , , и 40 other автор(ы). (октября 2020)bids-standard/pybids: 0.9.1., , , , , , , , , и 27 other автор(ы). (мая 2019)Can input reconstruction be used to directly estimate uncertainty of a regression U-Net model? - Application to proton therapy dose prediction for head and neck cancer patients., , , , и . CoRR, (2023)