psvn
Projected Stein Variational Newton: A Fast and Scalable Bayesian Inference Method in High Dimensions
Peng Chen, Keyi Wu, Joshua Chen, Tom O'Leary-Roseberry, Omar Ghattas
Contributions: In this work, we develop a projected Stein variational Newton method (pSVN) to tackle the challenge of high-dimensional Bayesian inference by exploiting the intrinsic lowdimensional geometric structure of the posterior distribution (where it departs from the prior), as characterized by the dominant spectrum of the prior-preconditioned Hessian of the negative log likelihood.
Country: North America > Canada > British Columbia > Metro Vancouver Regional District > Vancouver (0.04)
Technology:
Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (0.36)
Projected Stein Variational Newton: A Fast and Scalable Bayesian Inference Method in High Dimensions
Peng Chen, Keyi Wu, Joshua Chen, Tom O'Leary-Roseberry, Omar Ghattas
We propose a projected Stein variational Newton (pSVN) method for high-dimensional Bayesian inference.
Country:
- North America > United States > Texas > Travis County > Austin (0.14)
- North America > Canada (0.04)
Technology: Information Technology > Artificial Intelligence > Representation & Reasoning > Uncertainty > Bayesian Inference (0.86)
