Some more useful papers

[shantanu-ai]

Hi @aisagarw,

I want to contribute with these papers. Did not have the write access to create a branch and submit a pull request. So creating this issue, can u please add the following papers to this list.

• "Logic Explained Networks"
  Authors: Gabriele Ciravegna, Pietro Barbiero, Francesco Giannini, Marco Gori, Pietro Liò, Marco Maggini, Stefano Melacci
  Journal: Artificial Intelligence
  Summary: Logic Explained Networks (LENs) offer interpretable deep learning models that provide human-understandable explanations using First-Order Logic, outperforming traditional white-box models in both supervised and unsupervised learning tasks.

• "Entropy-based Logic Explanations of Neural Networks"
  Authors: Pietro Barbiero, Gabriele Ciravegna, Francesco Giannini, Pietro Lió, Marco Gori, Stefano Melacci
  Conference: AAAI 2022
  Summary: A novel end-to-end approach extracts concise First-Order Logic explanations from neural networks using an entropy-based criterion, improving both interpretability and classification accuracy in safety-critical domains.

• "Dividing and Conquering a BlackBox to a Mixture of Interpretable Models: Route, Interpret, Repeat"
  Authors: Shantanu Ghosh, Ke Yu, Forough Arabshahi, Kayhan Batmanghelich
  Conference: ICML 2023
  Summary: This paper introduces a method to iteratively carve concept-based interpretable models from a Blackbox in a post-hoc manner, using First Order Logic for explanations, while a residual network handles harder cases, achieving high interpretability without sacrificing performance.

• "Distilling BlackBox to Interpretable models for Efficient Transfer Learning"
  Authors: Shantanu Ghosh, Ke Yu, Forough Arabshahi, Kayhan Batmanghelich
  Conference: MICCAI 2023
  Summary: This paper presents an concept-based interpretable model for chest-X-ray classification that can be efficiently fine-tuned for new domains using minimal labeled data, leveraging semi-supervised learning and distillation from blackbox models.

Regards Shantanu

[shantanu-ai]

Sorry i just submitted the PR.