Interpretation Python Packages

shapley-lz

IN PROGRESS - after the paper "Shapley-Lorenz decompositions in eXplainable Artificial Intelligence" by Giudici and Raffinetti - 2020

acd

Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)

ensemble-integration

Ensemble Integration: a customizable pipeline for generating multi-modal, heterogeneous ensembles

lorenz-zonoid

IN PROGRESS - after the paper "Shapley-Lorenz decompositions in eXplainable Artificial Intelligence" by Giudici and Raffinetti - 2020

deepaccess

Methods for training and interpretation of an ensemble of neural networks for multi-task functional prediction of accessibility or histone modifications from DNA sequence.

interpret-pytorch

Interpreting Deep Neural Networks with PyTorch

structuredxtract

A new package is designed to simplify the process of extracting structured information from user-provided text inputs by leveraging a language model with pattern matching capabilities. The system prom

revelionn

Retrospective Extraction of Visual and Logical Insights for Ontology-based interpretation of Neural Networks