interpretable machine learning

Stochastic Concept Bottleneck Models NeurIPS 2024 Task-Driven Causal Feature Distillation: Towards Trustworthy Risk Prediction AAAI 2024 Thesis Summary: Operationalizing User-Inclusive Transparency in Artificial Intelligence Systems AAAI 2024 Through the MUD: A Multi-Defendant Charge Prediction Benchmark with Linked Crime Elements ACL 2024 Toward More Generalized Malicious URL Detection Models AAAI 2024 Towards Reducing Diagnostic Errors with Interpretable Risk Prediction NAACL 2024 ViTree: Single-Path Neural Tree for Step-Wise Interpretable Fine-Grained Visual Categorization AAAI 2024 VLG-CBM: Training Concept Bottleneck Models with Vision-Language Guidance NeurIPS 2024 Auxiliary Losses for Learning Generalizable Concept-based Models NeurIPS 2023 Building Concise Logical Patterns by Constraining Tsetlin Machine Clause Size IJCAI 2023 COCKATIEL: COntinuous Concept ranKed ATtribution with Interpretable ELements for explaining neural net classifiers on NLP ACL 2023 Combining Runtime Monitoring and Machine Learning with Human Feedback AAAI 2023 Computing Abductive Explanations for Boosted Regression Trees IJCAI 2023 Concept Correlation and Its Effects on Concept-Based Models WACV 2023 Dividing and Conquering a BlackBox to a Mixture of Interpretable Models: Route, Interpret, Repeat ICML 2023 Heavy Sets with Applications to Interpretable Machine Learning Diagnostics AISTATS 2023 Inherently Interpretable Multi-Label Classification Using Class-Specific Counterfactuals MIDL 2023 Interactive Concept Bottleneck Models AAAI 2023 Interpretable Chirality-Aware Graph Neural Network for Quantitative Structure Activity Relationship Modeling in Drug Discovery AAAI 2023 Interpretable differencing of machine learning models UAI 2023 Language in a Bottle: Language Model Guided Concept Bottlenecks for Interpretable Image Classification CVPR 2023 Learning to Receive Help: Intervention-Aware Concept Embedding Models NeurIPS 2023 NA^2Q: Neural Attention Additive Model for Interpretable Multi-Agent Q-Learning ICML 2023 Probabilistic Concept Bottleneck Models ICML 2023 REFER: An End-to-end Rationale Extraction Framework for Explanation Regularization CoNLL 2023