mlsanityData to 7 Oct 2026

Conditional Generative Models for Counterfactual Explanations

arXiv 2101.10123 ↗First posted 25 Jan 2021cs.LG stat.MLcited by 28

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Abstract (arXiv)

Counterfactual instances offer human-interpretable insight into the local behaviour of machine learning models. We propose a general framework to generate sparse, in-distribution counterfactual model explanations which match a desired target prediction with a conditional generative model, allowing batches of counterfactual instances to be generated with a single forward pass. The method is flexible with respect to the type of generative model used as well as the task of the underlying predictive model. This allows straightforward application of the framework to different modalities such as images, time series or tabular data as well as generative model paradigms such as GANs or autoencoders and predictive tasks like classification or regression. We illustrate the effectiveness of our method on image (CelebA), time series (ECG) and mixed-type tabular (Adult Census) data.

Key facts. Cited by 28 papers in the map (data through 7 Oct 2026). Builds on 26 of its 39 references that are in the map. First posted on arXiv 25 Jan 2021.

Builds on

26 of 39 references.

References · 26

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  3. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  4. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 5,986
  5. 2013Auto-Encoding Variational Bayescited by 3,980
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  7. 2016Categorical Reparameterization with Gumbel-Softmaxcited by 2,708
  8. 2018Large Scale GAN Training for High Fidelity Natural Image Synthesiscited by 2,609
  9. 2014Conditional Generative Adversarial Netscited by 2,152
  10. 2017Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPRcited by 1,086
  11. 2018Self-Attention Generative Adversarial Networkscited by 809
  12. 2019Modeling Tabular data using Conditional GANcited by 695
14 more
  1. 2019Explaining Machine Learning Classifiers through Diverse Counterfactual Explanationscited by 612
  2. 2016A Learned Representation For Artistic Stylecited by 340
  3. 2017Real-valued (Medical) Time Series Generation with Recurrent Conditional GANscited by 329
  4. 2018cGANs with Projection Discriminatorcited by 253
  5. 2018Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shiftcited by 240
  6. 2019Interpretable Counterfactual Explanations Guided by Prototypescited by 223
  7. 2018Adversarial Audio Synthesiscited by 222
  8. 2019Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifierscited by 143
  9. 2019Towards Realistic Individual Recourse and Actionable Explanations in Black-Box Decision Making Systemscited by 128
  10. 2020A U-Net Based Discriminator for Generative Adversarial Networkscited by 128
  11. 2020A survey of algorithmic recourse: definitions, formulations, solutions, and prospectscited by 118
  12. 2016Neural Photo Editing with Introspective Adversarial Networkscited by 109
  13. 2019Generative Counterfactual Introspection for Explainable Deep Learningcited by 36
  14. 2020Born Identity Network: Multi-way Counterfactual Map Generation to Explain a Classifier's Decisioncited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 3; 2022: 3; 2023: 5; 2024: 7; 2025: 5; 2026: 5.

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  1. 2021If Only We Had Better Counterfactual Explanations: Five Key Deficits to Rectify in the Evaluation of Counterfactual XAI Techniquescited by 82
  2. 2022Diffusion Models for Counterfactual Explanationscited by 79
  3. 2021Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanationscited by 56
  4. 2023Adversarial Counterfactual Visual Explanationscited by 47
  5. 2023Counterfactual Generative Models for Time-Varying Treatmentscited by 17
  6. 2021Model-agnostic and Scalable Counterfactual Explanations via Reinforcement Learningcited by 15
  7. 2022Generating Sparse Counterfactual Explanations For Multivariate Time Seriescited by 11
  8. 2022Counterfactual Image Synthesis for Discovery of Personalized Predictive Image Markerscited by 10
  9. 2024Shapelet-based Model-agnostic Counterfactual Local Explanations for Time Series Classificationcited by 6
  10. 2024Even-Ifs From If-Onlys: Are the Best Semi-Factual Explanations Found Using Counterfactuals As Guides?cited by 5
  11. 2024CountARFactuals -- Generating plausible model-agnostic counterfactual explanations with adversarial random forestscited by 5
  12. 2024Causal Generative Explainers using Counterfactual Inference: A Case Study on the Morpho-MNIST Datasetcited by 4
16 more
  1. 2024Generating Feasible and Plausible Counterfactual Explanations for Outcome Prediction of Business Processescited by 4
  2. 2026What-If Explanations Over Time: Counterfactuals for Time Series Classificationcited by 4
  3. 2023For Better or Worse: The Impact of Counterfactual Explanations' Directionality on User Behavior in xAIcited by 3
  4. 2024Relevant Irrelevance: Generating Alterfactual Explanations for Image Classifierscited by 3
  5. 2025Flexible Counterfactual Explanations with Generative Modelscited by 2
  6. 2025A Survey on Interpretability in Visual Recognitioncited by 2
  7. 2025Counterfactual Explanations for Time Series Should be Human-Centered and Temporally Coherent in Interventionscited by 2
  8. 2026Counterfactual Explanations on Robust Perceptual Geodesicscited by 2
  9. 2023Towards Explainable Land Cover Mapping: a Counterfactual-based Strategycited by 1
  10. 2025Counterfactual Visual Explanation via Causally-Guided Adversarial Steeringcited by 1
  11. 2026Counterfactual Maps: What They Are and How to Find Themcited by 1
  12. 2026A unified framework for evaluating the robustness of machine-learning interpretability for prospect riskingcited by 1
  13. 2023Personalized Path Recourse for Reinforcement Learning Agentscited by 0
  14. 2024Generating Realistic Adversarial Examples for Business Processes using Variational Autoencoderscited by 0
  15. 2025Match Chat: Real Time Generative AI and Generative Computing for Tenniscited by 0
  16. 2026Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Datacited by 0