[HTML][HTML] Machine learning in weather prediction and climate analyses—applications and perspectives
B Bochenek, Z Ustrnul - Atmosphere, 2022 - mdpi.com
In this paper, we performed an analysis of the 500 most relevant scientific articles published
since 2018, concerning machine learning methods in the field of climate and numerical …
since 2018, concerning machine learning methods in the field of climate and numerical …
Using an explainable machine learning approach to characterize earth system model errors: Application of SHAP analysis to modeling lightning flash occurrence
Computational models of the Earth System are critical tools for modern scientific inquiry.
Efforts toward evaluating and improving errors in representations of physical and chemical …
Efforts toward evaluating and improving errors in representations of physical and chemical …
Sensitivity of air pollution exposure and disease burden to emission changes in China using machine learning emulation
Abstract Machine learning models can emulate chemical transport models, reducing
computational costs and enabling more experimentation. We developed emulators to predict …
computational costs and enabling more experimentation. We developed emulators to predict …
[HTML][HTML] Limitations of XAI methods for process-level understanding in the atmospheric sciences
Explainable artificial intelligence (XAI) methods are becoming popular tools for scientific
discovery in the Earth and atmospheric sciences. While these techniques have the potential …
discovery in the Earth and atmospheric sciences. While these techniques have the potential …
Detection of forced change within combined climate fields using explainable neural networks
Assessing forced climate change requires the extraction of the forced signal from the
background of climate noise. Traditionally, tools for extracting forced climate change signals …
background of climate noise. Traditionally, tools for extracting forced climate change signals …
[HTML][HTML] Exploring Randomly Wired Neural Networks for Climate Model Emulation
Exploring the climate impacts of various anthropogenic emissions scenarios is key to
making informed decisions for climate change mitigation and adaptation. State-of-the-art …
making informed decisions for climate change mitigation and adaptation. State-of-the-art …
[HTML][HTML] Two-step hyperparameter optimization method: Accelerating hyperparameter search by using a fraction of a training dataset
Hyperparameter optimization (HPO) is an important step in machine learning (ML) model
development, but common practices are archaic—primarily relying on manual or grid …
development, but common practices are archaic—primarily relying on manual or grid …
[图书][B] Molecular Dynamics Simulations and Neural Network Solutions for Applications in Biophysics
A Nagel - 2022 - search.proquest.com
As computing resources evolved and became more accessible over time, much of scientific
research shifted towards utilizing computational techniques. In particular, biophysics is a …
research shifted towards utilizing computational techniques. In particular, biophysics is a …