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Shapley Additive Explanations

SHAP

Papers archive 2025-07-28

archive papers tagged: 550 · with a code link: 175 · where Syntology ran a sample: 26 (19 with a run with no instrument failure, 7 where every run was a failure of Syntology's instrument) Syntology

Show: all tagged papersonly where code ran (26 of 550 tagged: 19 with a run with no instrument failure, 7 where every run was a failure of Syntology's instrument)

Page 6 of 6: papers 501 to 550 of 550, newest first by the archive's date (ties by slug), in archive order.

Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code, as “N ran (of which C constructed an object rather than computing a result; K with no instrument failure: H honoured, V violated, P with no contract checked; I where Syntology's instrument failed) · U unverified”; the instrument figure counts failures of Syntology's instrument, not of the code. It is per sample and not a correctness claim. When the archive marks a repository official for the paper, the line starts with that repository's state (the archive's flag, not a verdict on who wrote the code; “community repositories only” when every sample that ran came from a community repository, “official: no sample here; runs from other or unrecorded repositories” when some came from a repository the paper names or has in its text, or from none recorded); hover it for the repositories the samples that ran came from.

• Evaluating Explainable Methods for Predictive Process Analytics: A Functionally-Grounded Approach
  8 Dec 2020 · 1 repository · arXiv:2012.04218
• BayLIME: Bayesian Local Interpretable Model-Agnostic Explanations
  5 Dec 2020 · 2 repositories · arXiv:2012.03058
• Explaining Deep Learning Models for Structured Data using Layer-Wise Relevance Propagation
  26 Nov 2020 · 0 repositories · arXiv:2011.13429
• PSD2 Explainable AI Model for Credit Scoring
  20 Nov 2020 · 0 repositories · arXiv:2011.10367
• An experiment on the mechanisms of racial bias in ML-based credit scoring in Brazil
  11 Nov 2020 · 0 repositories · arXiv:2011.09865
• Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same End
  10 Nov 2020 · 1 repository · arXiv:2011.04917
• GPUTreeShap: Massively Parallel Exact Calculation of SHAP Scores for Tree Ensembles
  27 Oct 2020 · 4 repositories · arXiv:2010.13972
  Syntology community repositories only · 4 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 2 honoured, 0 violated, 1 with no contract checked; 1 where Syntology's instrument failed) · 4 unverified (of 8 harvested samples)
• Quantitative and Qualitative Evaluation of Explainable Deep Learning Methods for Ophthalmic Diagnosis
  26 Sep 2020 · 0 repositories · arXiv:2009.12648
• On the Tractability of SHAP Explanations
  18 Sep 2020 · 0 repositories · arXiv:2009.08634
• Principles and Practice of Explainable Machine Learning
  18 Sep 2020 · 0 repositories · arXiv:2009.11698
• An explainable XGBoost-based approach towards assessing the risk of cardiovascular disease in patients with Type 2 Diabetes Mellitus
  14 Sep 2020 · 0 repositories · arXiv:2009.06629
• SNoRe: Scalable Unsupervised Learning of Symbolic Node Representations
  8 Sep 2020 · 1 repository · arXiv:2009.04535
• SHAP values for Explaining CNN-based Text Classification Models
  26 Aug 2020 · 0 repositories · arXiv:2008.11825
• White-box Induction From SVM Models: Explainable AI with Logic Programming
  9 Aug 2020 · 0 repositories · arXiv:2008.03301
• Closed-Form Expressions for Global and Local Interpretation of Tsetlin Machines with Applications to Explaining High-Dimensional Data
  27 Jul 2020 · 0 repositories · arXiv:2007.13885
• Machine Learning approach for Credit Scoring
  20 Jul 2020 · 0 repositories · arXiv:2008.01687
• timeXplain -- A Framework for Explaining the Predictions of Time Series Classifiers
  15 Jul 2020 · 1 repository · arXiv:2007.07606
  Syntology official (archive's flag): 9 ran · 9 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified (of 10 harvested samples)
• Accuracy Prediction with Non-neural Model for Neural Architecture Search
  9 Jul 2020 · 1 repository · arXiv:2007.04785
  Syntology official (archive's flag): 3 ran · 3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified (of 5 harvested samples) · 1 pointer-only (licence)
• Interpretable Visualizations with Differentiating Embedding Networks
  11 Jun 2020 · 1 repository · arXiv:2006.06640
• X-SHAP: towards multiplicative explainability of Machine Learning
  8 Jun 2020 · 0 repositories · arXiv:2006.04574
• The best way to select features?
  26 May 2020 · 0 repositories · arXiv:2005.12483
• An Investigation of COVID-19 Spreading Factors with Explainable AI Techniques
  5 May 2020 · 0 repositories · arXiv:2005.06612
• Explainable AI for Classification using Probabilistic Logic Inference
  5 May 2020 · 2 repositories · arXiv:2005.02074
• Investigating similarities and differences between South African and Sierra Leonean school outcomes using Machine Learning
  22 Apr 2020 · 0 repositories · arXiv:2004.11369
• Explainable Image Classification with Evidence Counterfactual
  16 Apr 2020 · 0 repositories · arXiv:2004.07511
• From text saliency to linguistic objects: learning linguistic interpretable markers with a multi-channels convolutional architecture
  7 Apr 2020 · 0 repositories · arXiv:2004.03254
• Fairness by Explicability and Adversarial SHAP Learning
  11 Mar 2020 · 0 repositories · arXiv:2003.05330
• Explaining Data-Driven Decisions made by AI Systems: The Counterfactual Approach
  21 Jan 2020 · 0 repositories · arXiv:2001.07417
• EMAP: Explanation by Minimal Adversarial Perturbation
  2 Dec 2019 · 0 repositories · arXiv:1912.00872
• Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods
  6 Nov 2019 · 2 repositories · arXiv:1911.02508
  Syntology official (archive's flag): 3 ran · 3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified (of 6 harvested samples)
• EnergyStar++: Towards more accurate and explanatory building energy benchmarking
  30 Oct 2019 · 1 repository · arXiv:1910.14563
• Feature relevance quantification in explainable AI: A causal problem
  29 Oct 2019 · 0 repositories · arXiv:1910.13413
• Do Explanations Reflect Decisions? A Machine-centric Strategy to Quantify the Performance of Explainability Algorithms
  16 Oct 2019 · 0 repositories · arXiv:1910.07387
• Measuring Unfairness through Game-Theoretic Interpretability
  12 Oct 2019 · 0 repositories · arXiv:1910.05591
• Induction of Non-monotonic Logic Programs To Explain Statistical Learning Models
  18 Sep 2019 · 0 repositories · arXiv:1909.09017
• The Explanation Game: Explaining Machine Learning Models Using Shapley Values
  17 Sep 2019 · 1 repository · arXiv:1909.08128
• Towards a Rigorous Evaluation of XAI Methods on Time Series
  16 Sep 2019 · 0 repositories · arXiv:1909.07082
• Deep neural network or dermatologist?
  19 Aug 2019 · 1 repository · arXiv:1908.06612
• Explaining Image Classifiers using Statistical Fault Localization
  6 Aug 2019 · 1 repository · arXiv:1908.02374
• Technical Report: Partial Dependence through Stratification
  15 Jul 2019 · 1 repository · arXiv:1907.06698
• A Human-Grounded Evaluation of SHAP for Alert Processing
  7 Jul 2019 · 0 repositories · arXiv:1907.03324
• Induction of Non-Monotonic Rules From Statistical Learning Models Using High-Utility Itemset Mining
  24 May 2019 · 1 repository · arXiv:1905.11226
• Explaining a prediction in some nonlinear models
  21 Apr 2019 · 0 repositories · arXiv:1904.09615
• Do Not Trust Additive Explanations
  27 Mar 2019 · 2 repositories · arXiv:1903.11420
  Syntology community repositories only · 3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 1 unverified (of 4 harvested samples)
• Explaining individual predictions when features are dependent: More accurate approximations to Shapley values
  25 Mar 2019 · 0 repositories · arXiv:1903.10464
• Explaining Anomalies Detected by Autoencoders Using SHAP
  6 Mar 2019 · 2 repositories · arXiv:1903.02407
• Explaining Machine Learning Models using Entropic Variable Projection
  18 Oct 2018 · 2 repositories · arXiv:1810.07924
• Convolutional Embedded Networks for Population Scale Clustering and Bio-ancestry Inferencing
  30 May 2018 · 4 repositories · arXiv:1805.12218
• Consistent feature attribution for tree ensembles
  19 Jun 2017 · 1 repository · arXiv:1706.06060
• A Unified Approach to Interpreting Model Predictions
  22 May 2017 · 17 repositories · arXiv:1705.07874
  Syntology 3 ran (of which 1 constructed an object rather than computing a result; 3 with no instrument failure: 1 honoured, 1 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 5 unverified (of 8 harvested samples) · 6 pointer-only (licence)