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Found 3 papers, 1 papers with code
Constrained Monotonic Neural Networks
Wider adoption of neural networks in many critical domains such as finance and healthcare is being hindered by the need to explain their predictions and to impose additional constraints on them.
Attention Augmented Convolutional Transformer for Tabular Time-series
Time-series classification is one of the most frequently performed tasks in industrial data science, and one of the most widely used data representation in the industrial setting is tabular representation.
ALIME: Autoencoder Based Approach for Local Interpretability
Inthis work, we propose a locally interpretable method, which is inspiredby one of the recent tools that has gained a lot of interest, called localinterpretable model-agnostic explanations (LIME).
