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Interpretability

7,318 papers

Papers per year

Papers

Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability NIPS 2022
Decision Trees with Short Explainable Rules NIPS 2022
RKHS-SHAP: Shapley Values for Kernel Methods NIPS 2022
Repairing Neural Networks by Leaving the Right Past Behind NIPS 2022
Constrained Predictive Coding as a Biologically Plausible Model of the Cortical Hierarchy NIPS 2022
Washing The Unwashable : On The (Im)possibility of Fairwashing Detection NIPS 2022
Where do Models go Wrong? Parameter-Space Saliency Maps for Explainability NIPS 2022
Task Discovery: Finding the Tasks that Neural Networks Generalize on NIPS 2022
OpenXAI: Towards a Transparent Evaluation of Model Explanations NIPS 2022
Normalizing Flows for Knockoff-free Controlled Feature Selection NIPS 2022
Inherently Explainable Reinforcement Learning in Natural Language NIPS 2022
Neural Topological Ordering for Computation Graphs NIPS 2022
CEBaB: Estimating the Causal Effects of Real-World Concepts on NLP Model Behavior NIPS 2022
Learning to Generate Inversion-Resistant Model Explanations NIPS 2022
If Influence Functions are the Answer, Then What is the Question? NIPS 2022
Probing Classifiers are Unreliable for Concept Removal and Detection NIPS 2022
SkinCon: A skin disease dataset densely annotated by domain experts for fine-grained debugging and analysis NIPS 2022
Convergent Representations of Computer Programs in Human and Artificial Neural Networks NIPS 2022
GStarX: Explaining Graph Neural Networks with Structure-Aware Cooperative Games NIPS 2022
AutoMS: Automatic Model Selection for Novelty Detection with Error Rate Control NIPS 2022
Chroma-VAE: Mitigating Shortcut Learning with Generative Classifiers NIPS 2022
Exploiting the Relationship Between Kendall's Rank Correlation and Cosine Similarity for Attribution Protection NIPS 2022
Additive MIL: Intrinsically Interpretable Multiple Instance Learning for Pathology NIPS 2022
Boosting Out-of-distribution Detection with Typical Features NIPS 2022
Evaluating Latent Space Robustness and Uncertainty of EEG-ML Models under Realistic Distribution Shifts NIPS 2022