From bdb7aa032c79337550259e1b7e7b51ef9ffdf033 Mon Sep 17 00:00:00 2001 From: Shan Carter Date: Mon, 28 Aug 2017 18:18:29 -0700 Subject: [PATCH] More authoritative-ness --- examples/article.html | 6 ++--- src/components/d-byline.js | 48 +++++++++++--------------------------- src/components/d-title.js | 12 +++++----- 3 files changed, 22 insertions(+), 44 deletions(-) diff --git a/examples/article.html b/examples/article.html index 2b7ee62..46b6106 100644 --- a/examples/article.html +++ b/examples/article.html @@ -9,7 +9,7 @@ title: Demo Title Attention and Augmented Recurrent Neural Networks published: Jan 10, 2017 authors: - - Chris Olah: + - Chris Olah: http://shancarter.com - Shan Carter: http://shancarter.com affiliations: - Google Brain @@ -21,8 +21,8 @@ -

Attention and Augmented Recurrent Neural Networks

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Although extremely useful for visualizing high-dimensional data, t-SNE plots can sometimes be mysterious or misleading. By exploring how it behaves in simple cases, we can learn to use it more effectively.

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How to Use t-SNE Effectively

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Although extremely useful for visualizing high-dimensional data, t-SNE plots can sometimes be mysterious or misleading.