5 papers
Testing Equality of Conditional Distributions via Generative Models
Hanjia Gao, Linjun Huang, Yun Yang +1
We study the problem of testing whether two conditional distributions are equal using generative models. The proposed method learns a conditional generator from each sample and use…
Transforming the Use of Earth Observation Data: Exascale Training of a Generative Compression Model with Historical Priors for up to 10,000x Data Reduction
Jinxiao Zhang, Runmin Dong, Xiyong Wu +14
Earth observation is becoming one of the largest data-producing activities in science, yet current pipelines still treat compression as a storage and transmission tool rather than…
Likelihood-Free Inference via Structured Score Matching
Haoyu Jiang, Yuexi Wang, Yun Yang
In many statistical problems, the data distribution is specified through a generative process for which the likelihood function is analytically intractable, yet inference on the as…
A Likelihood Based Approach to Distribution Regression Using Conditional Deep Generative Models
Shivam Kumar, Yun Yang, Lizhen Lin
In this work, we explore the theoretical properties of conditional deep generative models under the statistical framework of distribution regression where the response variable lie…
Conditional Diffusion Models are Minimax-Optimal and Manifold-Adaptive for Conditional Distribution Estimation
Rong Tang, Lizhen Lin, Yun Yang
We consider a class of conditional forward-backward diffusion models for conditional generative modeling, that is, generating new data given a covariate (or control variable). To f…