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Found 3 papers, 1 papers with code
Neural Operator: Is data all you need to model the world? An insight into the impact of Physics Informed Machine Learning
This article aims to provide a comprehensive insight into how data-driven approaches can complement conventional techniques to solve engineering and physics problems, while also noting some of the major pitfalls of machine learning-based approaches.
Quantifying Human Bias and Knowledge to guide ML models during Training
We introduce an experimental approach to dealing with such unbalanced datasets by including humans in the training process.
A Holistic Framework for Analyzing the COVID-19 Vaccine Debate
The Covid-19 pandemic has led to infodemic of low quality information leading to poor health decisions.
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