innsight

Interpretation methods for analyzing the behavior and individual predictions of modern neural networks in a three-step procedure: Converting the model, running the interpretation method, and visualizing the results. Implemented methods are, e.g., 'Connection Weights' described by Olden et al. (2004) doi:10.1016/j.ecolmodel.2004.03.013, layer-wise relevance propagation ('LRP') described by Bach et al. (2015) doi:10.1371/journal.pone.0130140, deep learning important features ('DeepLIFT') described by Shrikumar et al. (2017) doi:10.48550/arXiv.1704.02685 and gradient-based methods like 'SmoothGrad' described by Smilkov et al. (2017) doi:10.48550/arXiv.1706.03825, 'Gradient x Input' or 'Vanilla Gradient'. Details can be found in the accompanying scientific paper: Koenen & Wright (2024, Journal of Statistical Software, doi:10.18637/jss.v111.i08).

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