4 citations · 4 across the 2 of their papers we have counts for
5 papers
Bayesian Invariance Modeling of Multi-Environment Data
Luhuan Wu, Mingzhang Yin, Yixin Wang +2
Invariant prediction [Peters et al., 2016] analyzes feature/outcome data from multiple environments to identify invariant features - those with a stable predictive relationship to…
Robust Inference-Time Steering of Protein Diffusion Models via Embedding Optimization
Minhuan Li, Jiequn Han, Pilar Cossio +1
A core challenge in structural biophysics is generating biomolecular conformations that are both physically plausible and consistent with experimental measurements. While sequence-…
Reverse Diffusion Sequential Monte Carlo Samplers
Luhuan Wu, Yi Han, Christian A. Naesseth +1
We propose a novel sequential Monte Carlo (SMC) method for sampling from unnormalized target distributions based on a reverse denoising diffusion process. While recent diffusion-ba…
Practical and Asymptotically Exact Conditional Sampling in Diffusion Models
Luhuan Wu, Brian L. Trippe, Christian A. Naesseth +2
Diffusion models have been successful on a range of conditional generation tasks including molecular design and text-to-image generation. However, these achievements have primarily…
Variational Nearest Neighbor Gaussian Process
Luhuan Wu, Geoff Pleiss, John Cunningham
Variational approximations to Gaussian processes (GPs) typically use a small set of inducing points to form a low-rank approximation to the covariance matrix. In this work, we inst…