website

commit d688b2ba4bebc2404cf02ad8c8383be40cb2c20a
parent b8bd1c73178a4fdf968d82f77ebbd392c850ab35
Author: Silas Brack <57684859+silasbrack@users.noreply.github.com>
Date:   Thu, 22 May 2025 22:18:09 +0200

Fix sidenotes (#3)


Diffstat:
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index.html
 | 
6
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1 file changed, 4 insertions(+), 2 deletions(-)
diff --git a/index.html b/index.html
@@ -53,13 +53,15 @@
         <p>Previously, I've also worked as a C# developer at MAN Energy Solutions.</p>
         <p>
           I did my master's in Mathematical Modelling and Computation at the Technical University of Denmark. During my
-          thesis<label for="sn-in-his-later-books" class="margin-toggle sidenote-number"></label>,
+          thesis<label for="sn-thesis" class="margin-toggle sidenote-number"></label>,
+          <input type="checkbox" id="sn-thesis" class="margin-toggle"/>
           <span class="sidenote">
             <a href="./assets/thesis.pdf">“Effortless Bayesian Deep Learning: Tapping Into the Potential of Modern Optimizers”</a>
           </span>
           I worked on implicit matrix algorithms for performing the Laplace approximation in Søren Hauberg's
           group in the section for Cognitive Systems of DTU Compute. We also worked on applying the Laplace approximation to metric
-          learning, which we published at NeurIPS<label for="sn-in-his-later-books" class="margin-toggle sidenote-number"></label>.
+          learning, which we published at NeurIPS<label for="sn-metric-learning" class="margin-toggle sidenote-number"></label>.
+          <input type="checkbox" id="sn-metric-learning" class="margin-toggle"/>
           <span class="sidenote">
             <a href="https://arxiv.org/abs/2302.01332">“Bayesian Metric Learning for Uncertainty Quantification in Image Retrieval,”
             in <em>Advances in Neural Information Processing Systems</em>, 2023.</a>