Saved in:
| Main Authors: | Wettenstein, Ron, Mitchell, Rory, Yu, Peng |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2605.04497 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles
by: Muschalik, Maximilian, et al.
Published: (2024)
by: Muschalik, Maximilian, et al.
Published: (2024)
WOODELF-HD: Efficient Background SHAP for High-Depth Decision Trees
by: Wettenstein, Ron, et al.
Published: (2026)
by: Wettenstein, Ron, et al.
Published: (2026)
From Decision Trees to Boolean Logic: A Fast and Unified SHAP Algorithm
by: Nadel, Alexander, et al.
Published: (2025)
by: Nadel, Alexander, et al.
Published: (2025)
QuadraSHAP: Stable and Scalable Shapley Values for Product Games via Gauss-Legendre Quadrature
by: Mohammadi, Majid, et al.
Published: (2026)
by: Mohammadi, Majid, et al.
Published: (2026)
HyperSHAP: Shapley Values and Interactions for Explaining Hyperparameter Optimization
by: Wever, Marcel, et al.
Published: (2025)
by: Wever, Marcel, et al.
Published: (2025)
KernelSHAP-IQ: Weighted Least-Square Optimization for Shapley Interactions
by: Fumagalli, Fabian, et al.
Published: (2024)
by: Fumagalli, Fabian, et al.
Published: (2024)
Statistical Inference and Learning for Shapley Additive Explanations (SHAP)
by: Whitehouse, Justin, et al.
Published: (2026)
by: Whitehouse, Justin, et al.
Published: (2026)
Interaction Tensor SHAP
by: Hasegawa, Hiroki, et al.
Published: (2025)
by: Hasegawa, Hiroki, et al.
Published: (2025)
Woodelf++: A Fast and Unified Partial Dependence Plot Algorithm for Decision Tree Ensembles
by: Wettenstein, Ron, et al.
Published: (2026)
by: Wettenstein, Ron, et al.
Published: (2026)
PolySHAP: Extending KernelSHAP with Interaction-Informed Polynomial Regression
by: Fumagalli, Fabian, et al.
Published: (2026)
by: Fumagalli, Fabian, et al.
Published: (2026)
TN-SHAP-G: Graph-Structured Tensor Network Surrogates for Shapley Values and Interactions
by: Heidari, Farzaneh, et al.
Published: (2026)
by: Heidari, Farzaneh, et al.
Published: (2026)
InstaSHAP: Interpretable Additive Models Explain Shapley Values Instantly
by: Enouen, James, et al.
Published: (2025)
by: Enouen, James, et al.
Published: (2025)
CQD-SHAP: Explainable Complex Query Answering via Shapley Values
by: Abbasi, Parsa, et al.
Published: (2025)
by: Abbasi, Parsa, et al.
Published: (2025)
RankSHAP: Shapley Value Based Feature Attributions for Learning to Rank
by: Chowdhury, Tanya, et al.
Published: (2024)
by: Chowdhury, Tanya, et al.
Published: (2024)
Verified SHAP: Provable Bounds for Exact Shapley Values of Neural Networks
by: Boetius, David, et al.
Published: (2026)
by: Boetius, David, et al.
Published: (2026)
DeltaSHAP: Explaining Prediction Evolutions in Online Patient Monitoring with Shapley Values
by: Kim, Changhun, et al.
Published: (2025)
by: Kim, Changhun, et al.
Published: (2025)
TabSHAP
by: Chaudhary, Aryan, et al.
Published: (2026)
by: Chaudhary, Aryan, et al.
Published: (2026)
CS-SHAP: Extending SHAP to Cyclic-Spectral Domain for Better Interpretability of Intelligent Fault Diagnosis
by: Chen, Qian, et al.
Published: (2025)
by: Chen, Qian, et al.
Published: (2025)
ContextualSHAP : Enhancing SHAP Explanations Through Contextual Language Generation
by: Dwiyanti, Latifa, et al.
Published: (2025)
by: Dwiyanti, Latifa, et al.
Published: (2025)
Towards trustable SHAP scores
by: Letoffe, Olivier, et al.
Published: (2024)
by: Letoffe, Olivier, et al.
Published: (2024)
Improving the Weighting Strategy in KernelSHAP
by: Olsen, Lars Henry Berge, et al.
Published: (2024)
by: Olsen, Lars Henry Berge, et al.
Published: (2024)
GroupSegment-SHAP: Shapley Value Explanations with Group-Segment Players for Multivariate Time Series
by: Kim, Jinwoong, et al.
Published: (2026)
by: Kim, Jinwoong, et al.
Published: (2026)
Explanation Multiplicity in SHAP: Characterization and Assessment
by: Hwang, Hyunseung, et al.
Published: (2026)
by: Hwang, Hyunseung, et al.
Published: (2026)
Aumann-SHAP: The Geometry of Counterfactual Interaction Explanations in Machine Learning
by: Belahcen, Adam, et al.
Published: (2026)
by: Belahcen, Adam, et al.
Published: (2026)
SHAP-Guided Regularization in Machine Learning Models
by: Saadallah, Amal
Published: (2025)
by: Saadallah, Amal
Published: (2025)
SHAP values via sparse Fourier representation
by: Gorji, Ali, et al.
Published: (2024)
by: Gorji, Ali, et al.
Published: (2024)
Can Global XAI Methods Reveal Injected Bias in LLMs? SHAP vs Rule Extraction vs RuleSHAP
by: Sovrano, Francesco
Published: (2025)
by: Sovrano, Francesco
Published: (2025)
Fooling SHAP with Output Shuffling Attacks
by: Yuan, Jun, et al.
Published: (2024)
by: Yuan, Jun, et al.
Published: (2024)
SHAP-based Explanations are Sensitive to Feature Representation
by: Hwang, Hyunseung, et al.
Published: (2025)
by: Hwang, Hyunseung, et al.
Published: (2025)
From SHAP Scores to Feature Importance Scores
by: Letoffe, Olivier, et al.
Published: (2024)
by: Letoffe, Olivier, et al.
Published: (2024)
On the Tractability of SHAP Explanations under Markovian Distributions
by: Marzouk, Reda, et al.
Published: (2024)
by: Marzouk, Reda, et al.
Published: (2024)
ConfoundingSHAP: Quantifying confounding strength in causal inference
by: Brockschmidt, Marie, et al.
Published: (2026)
by: Brockschmidt, Marie, et al.
Published: (2026)
Interpretable Credit Default Prediction with Ensemble Learning and SHAP
by: Yang, Shiqi, et al.
Published: (2025)
by: Yang, Shiqi, et al.
Published: (2025)
$ϕ$-Table: A Statistical Explanation for Global SHAP
by: Kim, Dongseok, et al.
Published: (2025)
by: Kim, Dongseok, et al.
Published: (2025)
Towards Piece-by-Piece Explanations for Chess Positions with SHAP
by: Spinnato, Francesco
Published: (2025)
by: Spinnato, Francesco
Published: (2025)
SHLIME: Foiling adversarial attacks fooling SHAP and LIME
by: Chauhan, Sam, et al.
Published: (2025)
by: Chauhan, Sam, et al.
Published: (2025)
A comparative analysis of machine learning models in SHAP analysis
by: Lin, Justin, et al.
Published: (2026)
by: Lin, Justin, et al.
Published: (2026)
SHAP-Guided Kernel Actor-Critic for Explainable Reinforcement Learning
by: Li, Na, et al.
Published: (2025)
by: Li, Na, et al.
Published: (2025)
REFRESH: Responsible and Efficient Feature Reselection Guided by SHAP Values
by: Sharma, Shubham, et al.
Published: (2024)
by: Sharma, Shubham, et al.
Published: (2024)
Explainable time-series forecasting with sampling-free SHAP for Transformers
by: Hertel, Matthias, et al.
Published: (2025)
by: Hertel, Matthias, et al.
Published: (2025)
Similar Items
-
Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles
by: Muschalik, Maximilian, et al.
Published: (2024) -
WOODELF-HD: Efficient Background SHAP for High-Depth Decision Trees
by: Wettenstein, Ron, et al.
Published: (2026) -
From Decision Trees to Boolean Logic: A Fast and Unified SHAP Algorithm
by: Nadel, Alexander, et al.
Published: (2025) -
QuadraSHAP: Stable and Scalable Shapley Values for Product Games via Gauss-Legendre Quadrature
by: Mohammadi, Majid, et al.
Published: (2026) -
HyperSHAP: Shapley Values and Interactions for Explaining Hyperparameter Optimization
by: Wever, Marcel, et al.
Published: (2025)