no code implementations • 1 Feb 2024 • Sichao Li, Amanda Barnard
Explanations of machine learning models are important, especially in scientific areas such as chemistry, biology, and physics, where they guide future laboratory experiments and resource requirements.
Explainable artificial intelligence Explainable Artificial Intelligence (XAI)
1 code implementation • 30 May 2023 • Tommy Liu, Amanda Barnard
In this paper, we introduce the idea of decomposing the residuals of regression with respect to the data instances instead of features.
no code implementations • 17 May 2023 • Sichao Li, Rong Wang, Quanling Deng, Amanda Barnard
Thus, we recommend exploring feature interaction strengths in a model class of approximately equally accurate predictive models.
1 code implementation • 28 Sep 2022 • Sichao Li, Amanda Barnard
Black box models only provide results for deep learning tasks, and lack informative details about how these results were obtained.