Search Results for author: Xintian Han

Found 4 papers, 1 papers with code

X-CAL: Explicit Calibration for Survival Analysis

1 code implementation NeurIPS 2020 Mark Goldstein, Xintian Han, Aahlad Puli, Adler J. Perotte, Rajesh Ranganath

A survival model's calibration can be measured using, for instance, distributional calibration (D-CALIBRATION) [Haider et al., 2020] which computes the squared difference between the observed and predicted number of events within different time intervals.

Length-of-Stay prediction Survival Analysis

Explaining Data-Driven Decisions made by AI Systems: The Counterfactual Approach

no code implementations21 Jan 2020 Carlos Fernández-Loría, Foster Provost, Xintian Han

We examine counterfactual explanations for explaining the decisions made by model-based AI systems.

Feature Importance

Adversarial Examples for Electrocardiograms

no code implementations13 May 2019 Xintian Han, Yuxuan Hu, Luca Foschini, Larry Chinitz, Lior Jankelson, Rajesh Ranganath

For this model, we utilized a new technique to generate smoothed examples to produce signals that are 1) indistinguishable to cardiologists from the original examples and 2) incorrectly classified by the neural network.

Adversarial Defense Arrhythmia Detection +1

Kernelized Complete Conditional Stein Discrepancy

no code implementations9 Apr 2019 Raghav Singhal, Xintian Han, Saad Lahlou, Rajesh Ranganath

We introduce kernelized complete conditional Stein discrepancies (KCC-SDs).

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