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djgagne committed Aug 7, 2024
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7 changes: 3 additions & 4 deletions config.yml
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- parent : what
name : Education
url : education
weight : 1
weight : 3
- parent : what
name : Research
url : projects
weight : 2
weight : 3
weight : 1
- parent : what
name : Software
url : software
weight : 4
weight : 2
- name : Publications
url : publications
weight : 4
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24 changes: 0 additions & 24 deletions content/datasets/SPERR.md

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31 changes: 0 additions & 31 deletions content/news/20220801-projectpythia-hackathon.md

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14 changes: 0 additions & 14 deletions content/news/20221030-WildFire_Vapor_Visualization.md

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12 changes: 12 additions & 0 deletions content/news/20240520-siparcs.md
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---
title: "MILES Hosts 3 SIParCS Interns"
author: "David John Gagne"
date: 2024-05-20T12:00:00-06:00
type: news
image: images/blog/siparcs_2024.jpg
feature_image: images/blog/siparcs_2024.jpg
layout: staticpage
---

The MILES team is hosting 3 SIParCS interns for summer 2024 to work on uncertainty quantificiation, AI numerical weather prediction, and detecting cloud particles with holograms.

4 changes: 2 additions & 2 deletions content/software/milesguess.md
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---
title : "MILES GUESS"
date : 2023-04-05T12:00:00-06:00
date : 2024-08-01T12:00:00-06:00
type : software
tagline: "Generalized Uncertainty for Earth System Science (GUESS)"
docs : "https://pypi.org/project/miles-guess/"
repo : "https://github.com/NCAR/miles-guess"
image : "images/backgrounds/geocat-curly.png"
image : "images/projects/guess.png"
---

MILES GUESS provides Keras and Pytorch implementations of evidential deep learning models and supports analysis of aleatoric and epistemic uncertainties.
13 changes: 5 additions & 8 deletions data/whatwedo.yml
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title : WHAT WE DO
items :

- name : EDUCATION
quote: We host both undergraduate and graduate interns so that they can gain experience in machine learning applied to challenges in Earth system science.
url : education

- name : PROJECTS
- name : RESEARCH
quote: We conduct research aimed at improving our ability to apply rigorous, explainable, and quantifiable modeling to Earth system science challenges.
url : projects

- name : DATASETS
quote: We help the scientific community learn about and use available datasets responsibly.
url : datasets

- name : SOFTWARE
quote: We develop open source, community software that helps ML and atmospheric scientists run and optimize machine learning models.
url : software

- name : EDUCATION
quote: We host both undergraduate and graduate interns so that they can gain experience in machine learning applied to challenges in Earth system science.
url : education
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