4 papers · 1 filter
Learning Energy-Based Models from Stochastic Interpolants using Spatiotemporal Differences
Hanlin Yu, RuiKang OuYang, Partha Kaushik +3
Learning an energy-based model from data samples is a central problem in machine learning. Many recent and popular methods, such as denoising score matching for training energy-bas…
Neural Mutual Information Estimation with Vector Copulas
Yanzhi Chen, Zijing Ou, Adrian Weller +1
Estimating mutual information (MI) is a fundamental task in data science and machine learning. Existing estimators mainly rely on either highly flexible models (e.g., neural networ…
CFMI: Flow Matching for Missing Data Imputation
Vaidotas Simkus, Michael U. Gutmann
We introduce conditional flow matching for imputation (CFMI), a new general-purpose method to impute missing data. The method combines continuous normalising flows, flow-matching,…
Improving Variational Autoencoder Estimation from Incomplete Data with Mixture Variational Families
Vaidotas Simkus, Michael U. Gutmann
We consider the task of estimating variational autoencoders (VAEs) when the training data is incomplete. We show that missing data increases the complexity of the model's posterior…