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EXPLAINABLE ARTIFICIAL INTELLIGENCE, XAI 2025, PT II

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论文数19
被引数4
期刊论文 19
发表时间
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Explainable Bayesian Optimization
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delete2026-01-01
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deleteChakraborty, Tanmay; Wirth, Christian; Seifert, Christin
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Leveraging Influence Functions for Resampling Data in Physics-Informed Neural Networks利用影响函数在物理信息神经网络中重采样数据
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deleteNaujoks, Jonas R.; Krasowski, Aleksander; Weckbecker, Moritz; Yolcu, Galip Umit; Wiegand, Thomas; Lapuschkin, Sebastian; Samek, Wojciech; Klausen, Rene P.
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Counterfactual Shapley Values for Explaining Reinforcement Learning反事实Shapley值用于解释强化学习
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deleteShi, Yiwei; Liu, Weiru
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POMELO: Black-Box Feature Attribution with Full-Input, In-Distribution PerturbationsPOMELO：基于全输入、分布内扰动的黑箱特征归因
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deleteAdemi, Luan; Noppel, Maximilian; Wressnegger, Christian
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Detecting Concept Drift with SHapley Additive ExPlanations for Intelligent Model Retraining in Energy Generation Forecasting利用SHapley加性解释检测概念漂移，以实现能源发电预测中的智能模型重训练
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deleteTeixeira, Brigida; Pinto, Tiago; Vale, Zita
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Mathematical Foundation of Interpretable Equivariant Surrogate Models
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deleteColombini, Jacopo Joy; Bonchi, Filippo; Giannini, Francesco; Giannottil, Fosca; Pellungrini, Roberto; Frosini, Patrizio
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Extending Decision Predicate Graphs for Comprehensive Explanation of Isolation Forest扩展决策谓词图以全面解释孤立森林
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deleteCeschin, Matteo; Arrighi, Leonardo; Longo, Luca; Junior, Sylvio Barbon
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Interpreting the Structure of Multi-object Representations in Vision Encoders解读视觉编码器中多目标表示的结构
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deleteKhajuria, Tarun; Dias, Braian Olmiro; Domnich, Marharyta; Aru, Jaan
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Safe and Efficient Social Navigation Through Explainable Safety Regions Based on Topological Features基于拓扑特征的基于可解释安全区域的安全高效社会导航
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deleteToscano-Duran, Victor; Narteni, Sara; Carlevaro, Alberto; Guzzi, Jerome; Gonzalez-Diaz, Rocio; Mongelli, Maurizio
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Which LIME Should I Trust? Concepts, Challenges, and Solutions
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deleteKnab, Patrick; Marton, Sascha; Schlegel, Udo; Bartel, Christian
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A Biologically Inspired Filter Significance Assessment Method for Model Explanation一种受生物启发的滤波器显著性评估方法用于模型解释
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deleteBoge, Emirhan; Gunindi, Yasemin; Ertan, Murat Bilgehan; Aptoula, Erchan; Alp, Nihan; Ozkan, Huseyin
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Interpretable Link Prediction via Neural-Symbolic Reasoning基于神经符号推理的可解释链路预测
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deleteOntiveros, Rodrigo Castellano; Mobaraki, Ehsan Bonabi; Giannini, Francesco; Barbiero, Pietro; Cori, Marco; Diligenti, Michelangelo
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Bridging the Interpretability Gap in Process Mining: A Comprehensive Approach Combining Explainable Clustering and Generative AI在流程挖掘中弥合可解释性差距：一种结合可解释聚类和生成式AI的综合方法
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deleteAmling, Jonas; Slany, Emanuel; Dormagen, Christian; Kretschmann, Marco; Scheele, Stephan
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Balancing Fairness and Interpretability in Clustering with FairParTree在聚类中使用FairParTree平衡公平性与可解释性
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deleteLandi, Cristiano; Cascione, Alessio; Manerba, Marta Marchiori; Guidotti, Riccardo
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Improving the Weighting Strategy in KernelSHAP改进KernelSHAP中的加权策略
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deleteOlsen, Lars Henry Berge; Jullum, Martin
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Antithetic Sampling for Top-K Shapley Identification用于Top-K Shapley值识别的反演采样方法
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PREAI
deleteKolpaczki, Patrick; Nielen, Tim; Huellermeier, Eyke
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CFIRE: A General Method for Combining Local ExplanationsCFIRE：一种结合局部解释的通用方法
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deleteMueller, Sebastian; Toborek, Vanessa; Horvath, Tamas; Bauckhage, Christian
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CausalAIME: Leveraging Peter-Clark Algorithms and Inverse Modeling for Unified Global Feature Explanation in HealthcareCausalAIME：利用Peter-Clark算法和逆向建模实现医疗保健领域统一全局特征解释
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deleteNakanishi, Takafumi
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Explain to Gain: Introspective Reinforcement Learning for Enhanced Performance以解释促提升：用于增强性能的内省式强化学习
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deleteQuintana-Amate, Santiago; Stevens, Delaney; Ketheeswaran, Varniethan; Capaldo, Patrick; Sheldon, Dylan; Hall, Mark
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