Alert button
Picture for Brian L. Trippe

Brian L. Trippe

Alert button

Practical and Asymptotically Exact Conditional Sampling in Diffusion Models

Jun 30, 2023
Luhuan Wu, Brian L. Trippe, Christian A. Naesseth, David M. Blei, John P. Cunningham

Figure 1 for Practical and Asymptotically Exact Conditional Sampling in Diffusion Models
Figure 2 for Practical and Asymptotically Exact Conditional Sampling in Diffusion Models
Figure 3 for Practical and Asymptotically Exact Conditional Sampling in Diffusion Models
Figure 4 for Practical and Asymptotically Exact Conditional Sampling in Diffusion Models
Viaarxiv icon

Gaussian processes at the Helm(holtz): A more fluid model for ocean currents

Feb 20, 2023
Renato Berlinghieri, Brian L. Trippe, David R. Burt, Ryan Giordano, Kaushik Srinivasan, Tamay Özgökmen, Junfei Xia, Tamara Broderick

Figure 1 for Gaussian processes at the Helm(holtz): A more fluid model for ocean currents
Figure 2 for Gaussian processes at the Helm(holtz): A more fluid model for ocean currents
Figure 3 for Gaussian processes at the Helm(holtz): A more fluid model for ocean currents
Figure 4 for Gaussian processes at the Helm(holtz): A more fluid model for ocean currents
Viaarxiv icon

SE(3) diffusion model with application to protein backbone generation

Feb 11, 2023
Jason Yim, Brian L. Trippe, Valentin De Bortoli, Emile Mathieu, Arnaud Doucet, Regina Barzilay, Tommi Jaakkola

Figure 1 for SE(3) diffusion model with application to protein backbone generation
Figure 2 for SE(3) diffusion model with application to protein backbone generation
Figure 3 for SE(3) diffusion model with application to protein backbone generation
Figure 4 for SE(3) diffusion model with application to protein backbone generation
Viaarxiv icon

Diffusion probabilistic modeling of protein backbones in 3D for the motif-scaffolding problem

Jun 08, 2022
Brian L. Trippe, Jason Yim, Doug Tischer, Tamara Broderick, David Baker, Regina Barzilay, Tommi Jaakkola

Figure 1 for Diffusion probabilistic modeling of protein backbones in 3D for the motif-scaffolding problem
Figure 2 for Diffusion probabilistic modeling of protein backbones in 3D for the motif-scaffolding problem
Figure 3 for Diffusion probabilistic modeling of protein backbones in 3D for the motif-scaffolding problem
Figure 4 for Diffusion probabilistic modeling of protein backbones in 3D for the motif-scaffolding problem
Viaarxiv icon

Many processors, little time: MCMC for partitions via optimal transport couplings

Feb 23, 2022
Tin D. Nguyen, Brian L. Trippe, Tamara Broderick

Figure 1 for Many processors, little time: MCMC for partitions via optimal transport couplings
Figure 2 for Many processors, little time: MCMC for partitions via optimal transport couplings
Figure 3 for Many processors, little time: MCMC for partitions via optimal transport couplings
Figure 4 for Many processors, little time: MCMC for partitions via optimal transport couplings
Viaarxiv icon

For high-dimensional hierarchical models, consider exchangeability of effects across covariates instead of across datasets

Jul 13, 2021
Brian L. Trippe, Hilary K. Finucane, Tamara Broderick

Figure 1 for For high-dimensional hierarchical models, consider exchangeability of effects across covariates instead of across datasets
Figure 2 for For high-dimensional hierarchical models, consider exchangeability of effects across covariates instead of across datasets
Figure 3 for For high-dimensional hierarchical models, consider exchangeability of effects across covariates instead of across datasets
Figure 4 for For high-dimensional hierarchical models, consider exchangeability of effects across covariates instead of across datasets
Viaarxiv icon

LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations

May 17, 2019
Brian L. Trippe, Jonathan H. Huggins, Raj Agrawal, Tamara Broderick

Figure 1 for LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations
Figure 2 for LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations
Figure 3 for LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations
Figure 4 for LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations
Viaarxiv icon