Search Results for author: Paula Harder

Found 10 papers, 4 papers with code

Multi-variable Hard Physical Constraints for Climate Model Downscaling

no code implementations2 Aug 2023 Jose González-Abad, Álex Hernández-García, Paula Harder, David Rolnick, José Manuel Gutiérrez

Global Climate Models (GCMs) are the primary tool to simulate climate evolution and assess the impacts of climate change.

Identifying the Causes of Pyrocumulonimbus (PyroCb)

no code implementations16 Nov 2022 Emiliano Díaz Salas-Porras, Kenza Tazi, Ashwin Braude, Daniel Okoh, Kara D. Lamb, Duncan Watson-Parris, Paula Harder, Nis Meinert

A first causal discovery analysis from observational data of pyroCb (storm clouds generated from extreme wildfires) is presented.

Causal Discovery

Hard-Constrained Deep Learning for Climate Downscaling

1 code implementation8 Aug 2022 Paula Harder, Alex Hernandez-Garcia, Venkatesh Ramesh, Qidong Yang, Prasanna Sattigeri, Daniela Szwarcman, Campbell Watson, David Rolnick

In order to conserve physical quantities, here we introduce methods that guarantee statistical constraints are satisfied by a deep learning downscaling model, while also improving their performance according to traditional metrics.


Physics-Informed Learning of Aerosol Microphysics

no code implementations24 Jul 2022 Paula Harder, Duncan Watson-Parris, Philip Stier, Dominik Strassel, Nicolas R. Gauger, Janis Keuper

The original M7 model is used to generate data of input-output pairs to train a neural network on it.

Detecting AutoAttack Perturbations in the Frequency Domain

2 code implementations ICML Workshop AML 2021 Peter Lorenz, Paula Harder, Dominik Strassel, Margret Keuper, Janis Keuper

Recently, adversarial attacks on image classification networks by the AutoAttack (Croce and Hein, 2020b) framework have drawn a lot of attention.

Image Classification

Emulating Aerosol Microphysics with Machine Learning

no code implementations22 Sep 2021 Paula Harder, Duncan Watson-Parris, Dominik Strassel, Nicolas Gauger, Philip Stier, Janis Keuper

This is done in the ECHAM-HAM global climate aerosol model using the M7 microphysics model, but increased computational costs make it very expensive to run at higher resolutions or for a longer time.

BIG-bench Machine Learning

SpectralDefense: Detecting Adversarial Attacks on CNNs in the Fourier Domain

3 code implementations4 Mar 2021 Paula Harder, Franz-Josef Pfreundt, Margret Keuper, Janis Keuper

Despite the success of convolutional neural networks (CNNs) in many computer vision and image analysis tasks, they remain vulnerable against so-called adversarial attacks: Small, crafted perturbations in the input images can lead to false predictions.

Adversarial Attack

Cannot find the paper you are looking for? You can Submit a new open access paper.