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TitleStatusHype
Improving Confidence in the Estimation of Values and Norms—0
Counterfactual Multi-Agent Reinforcement Learning with Graph Convolution Communication—0
Quantifying the Economic Impact of Extreme Shocks on Businesses using Human Mobility Data: a Bayesian Causal Inference Approach—0
Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems—0
Plausible Counterfactuals: Auditing Deep Learning Classifiers with Realistic Adversarial Examples—0
Robust and On-the-fly Dataset Denoising for Image Classification—0
G-Net: A Deep Learning Approach to G-computation for Counterfactual Outcome Prediction Under Dynamic Treatment Regimes—0
ParKCa: Causal Inference with Partially Known CausesCode0
Fair inference on error-prone outcomes—0
Vector logic allows counterfactual virtualization by The Square Root of NOT—0
ViCE: Visual Counterfactual Explanations for Machine Learning ModelsCode0
What went wrong and when? Instance-wise Feature Importance for Time-series Models—0
Explaining Groups of Points in Low-Dimensional RepresentationsCode0
Counterfactual fairness: removing direct effects through regularization—0
On The Reasons Behind Decisions—0
Debiased Off-Policy Evaluation for Recommendation Systems—0
Learning Global Transparent Models Consistent with Local Contrastive Explanations—0
Stochastic Regret Minimization in Extensive-Form Games—0
Wireless Power Control via Counterfactual Optimization of Graph Neural Networks—0
Convex Density Constraints for Computing Plausible Counterfactual ExplanationsCode0
`Why didn't you allocate this task to them?' Negotiation-Aware Explicable Task Allocation and Contrastive Explanation Generation—0
Safe Exploration for Optimizing Contextual BanditsCode0
Estimating Welfare Effects in a Nonparametric Choice Model: The Case of School Vouchers—0
Empirical Analysis of Fictitious Play for Nash Equilibrium Computation in Multiplayer Games—0
Correcting for Selection Bias in Learning-to-rank Systems—0
One Explanation Does Not Fit All: The Promise of Interactive Explanations for Machine Learning Transparency—0
On the Fairness of Randomized Trials for Recommendation with Heterogeneous Demographics and Beyond—0
Explaining Data-Driven Decisions made by AI Systems: The Counterfactual Approach—0
Adequate and fair explanations—0
Distributional synthetic controls—0
Algorithms in Multi-Agent Systems: A Holistic Perspective from Reinforcement Learning and Game Theory—0
Probabilistic Reasoning across the Causal Hierarchy—0
The Counterfactual χ-GAN—0
Revealing Neural Network Bias to Non-Experts Through Interactive Counterfactual Examples—0
Minimal entropy production due to constraints on rate matrix dependencies in multipartite processes—0
Rational Inattention and Perceptual Distance—0
Counterfactual Evaluation of Treatment Assignment Functions with Networked Observational Data—0
Optimal Dynamic Treatment Regimes and Partial Welfare Ordering—0
Reducing Selection Bias in Counterfactual Reasoning for Individual Treatment Effects Estimation—0
Explaining Classifiers using Adversarial Perturbations on the Perceptual Ball—0
Counterfactual thinking in cooperation dynamics—0
Learning from Discriminatory Training Data—0
Estimation of Auction Models with Shape Restrictions—0
Peek Inside the Closed World: Evaluating Autoencoder-Based Detection of DDoS to Cloud—0
MetaCI: Meta-Learning for Causal Inference in a Heterogeneous Population—0
Exploratory Not Explanatory: Counterfactual Analysis of Saliency Maps for Deep Reinforcement Learning—0
Alternative Function Approximation Parameterizations for Solving Games: An Analysis of f-Regression Counterfactual Regret Minimization—0
Counterfactual Explanation Algorithms for Behavioral and Textual DataCode0
EMAP: Explanation by Minimal Adversarial Perturbation—0
Deep representation learning for individualized treatment effect estimation using electronic health recordsCode0
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