Public facing deeplift repo

SyReNN: Symbolic Representations for Neural Networks

Integrated gradients attribution method implemented in PyTorch

Attribution methods that explain image classification models, implemented in PyTorch, and support batch inputs and GPU.

simple implementation of Expected Gradients and Integrated Gradients by pytorch

Code and data for the ACL 2023 NLReasoning Workshop paper "Saliency Map Verbalization: Comparing Feature Importance Representations from Model-free and Instruction-based Methods" (Feldhus et al., 2023)

Scripts to reproduce results within the following manuscript: Perez, I., Skalski, P., Barns-Graham, A., Wong, J. and Sutton, D. (2022) Attribution of Predictive Uncertainties in Classification Models, 38th Conference on Uncertainty in Artificial Intelligence (UAI), Eindhoven, Netherlands, 2022.

Neural network visualization tool after an optional model compression with parameter pruning: (integrated) gradients, guided/visual backpropagation, activation maps for the cao model on the IndianPines dataset

To explain clinical BERT model predictions, we present an approach which leverages integrated gradients to attribute events in medical records that lead to an outcome prediction.

Exercise on interpretability with integrated gradients.

This repository is the code basis for the paper titled "Balancing Privacy and Explainability in Federated Learning"

TeleXGI: Explainable Gastrointestinal Image Classification for TeleSurgery Systems