13 citations · 30 across the 9 of their papers we have counts for
5 papers · 1 filter
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-…
Denoising Deep Generative Models
Gabriel Loaiza-Ganem, Brendan Leigh Ross, Luhuan Wu +3
Likelihood-based deep generative models have recently been shown to exhibit pathological behaviour under the manifold hypothesis as a consequence of using high-dimensional densitie…
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…
Hierarchical Inducing Point Gaussian Process for Inter-domain Observations
Luhuan Wu, Andrew Miller, Lauren Anderson +3
We examine the general problem of inter-domain Gaussian Processes (GPs): problems where the GP realization and the noisy observations of that realization lie on different domains.…
Bias-Free Scalable Gaussian Processes via Randomized Truncations
Andres Potapczynski, Luhuan Wu, Dan Biderman +2
Scalable Gaussian Process methods are computationally attractive, yet introduce modeling biases that require rigorous study. This paper analyzes two common techniques: early trunca…