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CounterFactual-XAI-Tutorials-and-Papers

CFX (CounterFactual eXplanation) is a popular method for model explanation. It is a post-hoc way that can give actionable explanations to a model result. In this repo, I will list out some SOTA related to CFX.

Notes: latest work are marked with fire πŸ”₯

πŸ“– Model explanation packages and libraries

DiCE [repo]

  • Explaining machine learning classifiers through diverse counterfactual explanations [paper]

Alibi [repo]

πŸ“š Survey paper

  • (arthur.ai) Counterfactual Explanations for Machine Learning: A Review [paper][ppt]
    • Evaluation of Counterfactual Generation Algorithms [Google Sheet]
  • Benchmarking and Survey of Explanation Methods for Black Box Models [paper]

πŸ’‘ Methods and works for different models

Model-Agnostic Methods

  • DiCE [example code]
    • Randomized sampling
    • KD-Tree (for counterfactuals within the training data)
    • Genetic algorithm
  • CFRL by Seldon Alibi [example code] [doc]
    • πŸ”₯ Model-agnostic and Scalable Counterfactual Explanations via Reinforcement Learning [paper]

Liz's Reading list (tba)

  • (Nips 2021) Designing Counterfactual Generators using Deep Model Inversion [paper]
    • No need training data
  • (Nips 2021) Towards Robust and Reliable Algorithmic Recourse [paper]
    • Data shifting
    • Adversarial training
  • (KDD 2021) Model-Based Counterfactual Synthesizer for Interpretation [paper]
  • CounteRGAN: Generating Realistic Counterfactuals with Residual Generative Adversarial Nets [paper]
  • (ICLR 2021) Counterfactual generative networks [paper][source code]
  • (AAAI 2022) Amortized Generation of Sequential Algorithmic Recourses for Black-box Models[paper]
    • Algorithmic Recourses (AR) and sequential ARs
    • Reinforcement learning
  • (AAAI 2022) Diverse, Global and Amortised Counterfactual Explanations for Uncertainty Estimates [paper]

πŸ₯Ά on-going

  • (PMLR 2020) Model-Agnostic Counterfactual Explanations for Consequential Decisions [paper] source code]
  • (FAT 2020) The Hidden Assumptions Behind Counterfactual Explanations and Principal Reasons [paper]

Gradient-Based Methods

  • CounterFactual (by Seldon Alibi) [example code] [doc]
    • Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR [paper]
  • CEM (By Seldon Alibi) [example code] [doc]
    • Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives [paper] [source code]
  • DiCE
  • πŸ”₯ GeCo: Quality Counterfactual Explanations in Real Time [paper] [source code]

Model-Specific Methods

CFX on Others

  • KS Test
    • πŸ”₯ Comprehensible Counterfactual Explanation on Kolmogorov-Smirnov Test [paper] [source code]

πŸ“Ί Tutorials and Discussions

  • Post-hoc counterfactual generation with supervised autoencoder [ppt]
  • If Only We Had Better Counterfactual Explanations: Five Key Deficits to Rectify in the Evaluation of Counterfactual XAI Techniques [paper]

πŸ‘©β€πŸ« Interdisciplinary Works Towards CFX

  • Adquate and Fair Explanations [paper]

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