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Found 5 papers, 4 papers with code
Learning Directed Graphical Models with Optimal Transport
Estimating the parameters of a probabilistic directed graphical model from incomplete data remains a long-standing challenge.
Transformed Distribution Matching for Missing Value Imputation
The key to missing value imputation is to capture the data distribution with incomplete samples and impute the missing values accordingly.
Feature-based Learning for Diverse and Privacy-Preserving Counterfactual Explanations
Interpretable machine learning seeks to understand the reasoning process of complex black-box systems that are long notorious for lack of explainability.
Variational Network Inference: Strong and Stable with Concrete Support
Traditional methods for the discovery of latent network structures are limited in two ways: they either assume that all the signal comes from the network (i. e. there is no source of signal outside the network) or they place constraints on the network parameters to ensure model or algorithmic stability.
Efficient Inference in Multi-task Cox Process Models
We generalize the log Gaussian Cox process (LGCP) framework to model multiple correlated point data jointly.
