Units-ML
Summary of the work in the work "Multidimensional Belief Quantification for label-efficient meta-learning"
In this work, we develop a novel computationally-efficient uncertainty-aware meta-learning model. We show the effectiveness of the uncertainty information using various experiments.
This work is based on Evidential Deep Learning work (see blog for details), and focuses on optimization-based meta-learning. However, extension to other meta-learning approaches such as metric-based meta-learning should be straightforward.
To give your project a background in the portfolio page, just add the img tag to the front matter like so:
---
layout: page
title: project
description: a project with a background image
img: /assets/img/12.jpg
---
You can also put regular text between your rows of images. Say you wanted to write a little bit about your project before you posted the rest of the images. You describe how you toiled, sweated, bled for your project, and then… you reveal its glory in the next row of images.
The code is simple. Just wrap your images with <div class="col-sm">
and place them inside <div class="row">
(read more about the Bootstrap Grid system). To make images responsive, add img-fluid
class to each; for rounded corners and shadows use rounded
and z-depth-1
classes. Here’s the code for the last row of images above:
<div class="row justify-content-sm-center">
<div class="col-sm-8 mt-3 mt-md-0">
{% include figure.html path="assets/img/6.jpg" title="example image" class="img-fluid rounded z-depth-1" %}
</div>
<div class="col-sm-4 mt-3 mt-md-0">
{% include figure.html path="assets/img/11.jpg" title="example image" class="img-fluid rounded z-depth-1" %}
</div>
</div>