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  1. Home
  2. /Repositories
  3. /explainX/explainx
Read original ↗
repoGitHubTrust 82 · PrimaryPublished 3d agoLive · 3d ago

explainX/explainx

Explain & debug any blackbox machine learning model with a single line of code.

Lineage graph

Paper → model → repo connections mined from source citations (Tier-1 exact match).

Why these links exist

Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.

  • PossiblePossibly related (embedding) · 55%ExplAIner: A Declarative Query Language for Explaining Classification Models →
  • PossiblePossibly related (embedding) · 54%Steering Neural Network Training through Interpretable Constraints Based on Partial Dependence →
  • PossiblePossibly related (embedding) · 52%All Explanations are Wrong, But Many Are Useful: Exploring the Rashomon Explanation Set with Large Language Models →
  • PossiblePossibly related (embedding) · 50%AgentTrace →
  • PossiblePossibly related (embedding) · 46%Scientific Explanations in Health Sciences: Causality, Trust, and Epistemic Adequacy →
  • PossiblePossibly related (embedding) · 48%Evaluating RE Practices for Explainability: Synthesizing Insights from Daimler Truck into an Explainable RE Framework Proposal →

Implements

paperExplAIner: A Declarative Query Language for Explaining Classification ModelspaperSteering Neural Network Training through Interpretable Constraints Based on Partial DependencepaperAll Explanations are Wrong, But Many Are Useful: Exploring the Rashomon Explanation Set with Large Language ModelspaperScientific Explanations in Health Sciences: Causality, Trust, and Epistemic Adequacy

Related to

toolAgentTrace

Implements (incoming)

paperEvaluating RE Practices for Explainability: Synthesizing Insights from Daimler Truck into an Explainable RE Framework Proposal

Related across the graph

paperSteering Neural Network Training through Interpretable Constraints Based on Partial DependencepaperExplAIner: A Declarative Query Language for Explaining Classification ModelspaperAll Explanations are Wrong, But Many Are Useful: Exploring the Rashomon Explanation Set with Large Language ModelspaperEvaluating RE Practices for Explainability: Synthesizing Insights from Daimler Truck into an Explainable RE Framework ProposalpaperScientific Explanations in Health Sciences: Causality, Trust, and Epistemic AdequacytoolAgentTrace
Knowledge path·PSteering Neural Network Training through Interpretable Constraints Based on Partial Dependence→PExplAIner: A Declarative Query Language for Explaining Classification Models→PAll Explanations are Wrong, But Many Are Useful: Exploring the Rashomon Explanation Set with Large Language Models→RexplainX/explainx

Topics

aws-sagemakerbiasblackboxexplainabilityexplainable-aiexplainable-artificial-intelligenceexplainable-mlexplainxinterpretabilityinterpretable-ai

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Graph trust82Primary
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