Brian L. Trippe

Publication Activity (10 Years)

Years Active: 2019-2023
Publications (10 Years): 15

Top Topics

Gaussian Process

Probabilistic Modeling

Diffusion Models

High Dimensions

Top Venues

Publications

Brian L. Trippe, Jason Yim, Doug Tischer, David Baker, Tamara Broderick, Regina Barzilay, Tommi S. Jaakkola
Diffusion Probabilistic Modeling of Protein Backbones in 3D for the motif-scaffolding problem. ICLR (2023)
Luhuan Wu, Brian L. Trippe, Christian A. Naesseth, David M. Blei, John P. Cunningham
Practical and Asymptotically Exact Conditional Sampling in Diffusion Models. CoRR (2023)
Luhuan Wu, Brian L. Trippe, Christian A. Naesseth, David M. Blei, John P. Cunningham
Practical and Asymptotically Exact Conditional Sampling in Diffusion Models. NeurIPS (2023)
Renato Berlinghieri, Brian L. Trippe, David R. Burt, Ryan James Giordano, Kaushik Srinivasan, Tamay M. Özgökmen, Junfei Xia, Tamara Broderick
Gaussian processes at the Helm(holtz): A more fluid model for ocean currents. ICML (2023)
Jason Yim, Brian L. Trippe, Valentin De Bortoli, Emile Mathieu, Arnaud Doucet, Regina Barzilay, Tommi S. Jaakkola
SE(3) diffusion model with application to protein backbone generation. ICML (2023)
Jason Yim, Brian L. Trippe, Valentin De Bortoli, Emile Mathieu, Arnaud Doucet, Regina Barzilay, Tommi S. Jaakkola
SE(3) diffusion model with application to protein backbone generation. CoRR (2023)
Renato Berlinghieri, Brian L. Trippe, David R. Burt, Ryan Giordano, Kaushik Srinivasan, Tamay M. Özgökmen, Junfei Xia, Tamara Broderick
Gaussian processes at the Helm(holtz): A more fluid model for ocean currents. CoRR (2023)
Tin D. Nguyen, Brian L. Trippe, Tamara Broderick
Many processors, little time: MCMC for partitions via optimal transport couplings. AISTATS (2022)
Brian L. Trippe, Jason Yim, Doug Tischer, David Baker, Tamara Broderick, Regina Barzilay, Tommi Jaakkola
Diffusion probabilistic modeling of protein backbones in 3D for the motif-scaffolding problem. CoRR (2022)
Brian L. Trippe, Hilary K. Finucane, Tamara Broderick
For high-dimensional hierarchical models, consider exchangeability of effects across covariates instead of across datasets. NeurIPS (2021)
Brian L. Trippe, Hilary K. Finucane, Tamara Broderick
For high-dimensional hierarchical models, consider exchangeability of effects across covariates instead of across datasets. CoRR (2021)
Brian L. Trippe, Jonathan H. Huggins, Raj Agrawal, Tamara Broderick
LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations. ICML (2019)
Brian L. Trippe, Jonathan H. Huggins, Raj Agrawal, Tamara Broderick
LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations. CoRR (2019)
Raj Agrawal, Brian L. Trippe, Jonathan H. Huggins, Tamara Broderick
The Kernel Interaction Trick: Fast Bayesian Discovery of Pairwise Interactions in High Dimensions. ICML (2019)
Raj Agrawal, Jonathan H. Huggins, Brian L. Trippe, Tamara Broderick
The Kernel Interaction Trick: Fast Bayesian Discovery of Pairwise Interactions in High Dimensions. CoRR (2019)