interpretable machine learning

UNIREX: A Unified Learning Framework for Language Model Rationale Extraction ICML 2022 Accurate and Interpretable Machine Learning for Transparent Pricing of Health Insurance Plans AAAI 2021 A Framework to Learn with Interpretation NeurIPS 2021 Connecting Interpretability and Robustness in Decision Trees through Separation ICML 2021 Explainable Models with Consistent Interpretations AAAI 2021 Explaining A Black-box By Using A Deep Variational Information Bottleneck Approach AAAI 2021 Explaining Hyperparameter Optimization via Partial Dependence Plots NeurIPS 2021 Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties AISTATS 2021 Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations. AISTATS 2021 Hybrid Predictive Models: When an Interpretable Model Collaborates with a Black-box Model JMLR 2021 Interpretable Actions: Controlling Experts with Understandable Commands AAAI 2021 Interpretable Random Forests via Rule Extraction AISTATS 2021 Learning Interpretable Decision Rule Sets: A Submodular Optimization Approach NeurIPS 2021 Neural Additive Models: Interpretable Machine Learning with Neural Nets NeurIPS 2021 Reasoning-Based Learning of Interpretable ML Models IJCAI 2021 TabNet: Attentive Interpretable Tabular Learning AAAI 2021 TripleTree: A Versatile Interpretable Representation of Black Box Agents and their Environments AAAI 2021 VisioRed: A Visualisation Tool for Interpretable Predictive Maintenance IJCAI 2021 Adversarial Dynamic Shapelet Networks AAAI 2020 Advisable Learning for Self-Driving Vehicles by Internalizing Observation-to-Action Rules CVPR 2020 An Evaluation of the Doctor-Interpretability of Generalized Additive Models with Interactions MLHC 2020 Born-Again Tree Ensembles ICML 2020 Concept Bottleneck Models ICML 2020 Explaining Groups of Points in Low-Dimensional Representations ICML 2020 Generalized and Scalable Optimal Sparse Decision Trees ICML 2020