sensitivity analysis

Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding ICML 2021 Sensitivity Analysis for Causal Mediation through Text: an Application to Political Polarization EMNLP 2021 Uncertainty-aware sensitivity analysis using Rényi divergences UAI 2021 Coresets for Regressions with Panel Data NeurIPS 2020 Efficient Predictive Uncertainty Estimators for Deep Probabilistic Models AAAI 2020 Evaluating and Aggregating Feature-based Model Explanations IJCAI 2020 Fairness Evaluation in Presence of Biased Noisy Labels AISTATS 2020 Learning Sensitivity of RCPSP by Analyzing the Search Process IJCAI 2020 Model-Preserving Sensitivity Analysis for Families of Gaussian Distributions JMLR 2020 Monte Carlo Gradient Estimation in Machine Learning JMLR 2020 SAM: The Sensitivity of Attribution Methods to Hyperparameters CVPR 2020 Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved Confounding NeurIPS 2020 The Discrete Gaussian for Differential Privacy NeurIPS 2020 Towards practical differentially private causal graph discovery NeurIPS 2020 Active Manifolds: A non-linear analogue to Active Subspaces ICML 2019 Assessing Disparate Impact of Personalized Interventions: Identifiability and Bounds NeurIPS 2019 Bayesian Parameter Estimation for Nonlinear Dynamics Using Sensitivity Analysis IJCAI 2019 Sensitivity Analysis of Deep Neural Networks AAAI 2019 Sensitivity Analysis of Linear Structural Causal Models ICML 2019 The Sensitivity of Counterfactual Fairness to Unmeasured Confounding UAI 2019 Variable selection for Gaussian processes via sensitivity analysis of the posterior predictive distribution AISTATS 2019 A Real-Time Game Theoretic Planner for Autonomous Two-Player Drone Racing RSS 2018 Confounding-Robust Policy Improvement NeurIPS 2018 INSPECTRE: Privately Estimating the Unseen ICML 2018 A Sensitivity Analysis of (and Practitioners’ Guide to) Convolutional Neural Networks for Sentence Classification IJCNLP 2017