4 papers
Robust Bayesian Inference on Riemannian Submanifold
Rong Tang, Anirban Bhattacharya, Debdeep Pati +1
Manifold-valued parameters routinely arise in modern statistical applications such as in medical imaging, robotics, and computer vision, to name a few. While traditional Bayesian a…
Minimax Optimal Rates for Regression on Manifolds and Distributions
Rong Tang, Yun Yang
Distribution regression seeks to estimate the conditional distribution of a multivariate response given a continuous covariate. This approach offers a more complete characterizatio…
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…
On the Computational Complexity of Metropolis-Adjusted Langevin Algorithms for Bayesian Posterior Sampling
Rong Tang, Yun Yang
In this paper, we examine the computational complexity of sampling from a Bayesian posterior (or pseudo-posterior) using the Metropolis-adjusted Langevin algorithm (MALA). MALA fir…