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Found 6 papers, 0 papers with code
Feature Attribution with Necessity and Sufficiency via Dual-stage Perturbation Test for Causal Explanation
In order to enhance the ability of FAMs to distinguish different features' contributions in this challenging setting, we propose to utilize the Probability of Necessity and Sufficiency (PNS) that perturbing a feature is a necessary and sufficient cause for the prediction to change as a measure of feature importance.
Graph Neural Stochastic Differential Equations
We present a novel model Graph Neural Stochastic Differential Equations (Graph Neural SDEs).
Educational Question Mining At Scale: Prediction, Analysis and Personalization
Online education platforms enable teachers to share a large number of educational resources such as questions to form exercises and quizzes for students.
HM-VAEs: a Deep Generative Model for Real-valued Data with Heterogeneous Marginals
In this paper, we focused on improving VAEs for real-valued data that has heterogeneous marginal distributions.
Ambiguity Helps: Classification With Disagreements in Crowdsourced Annotations
On the technical side, we propose a framework to incorporate annotation disagreements into the classifiers.
Stochastic Expectation Propagation
Expectation propagation (EP) is a deterministic approximation algorithm that is often used to perform approximate Bayesian parameter learning.
