no code implementations • 13 Apr 2023 • Javier Burroni, Justin Domke, Daniel Sheldon
We present a novel approach for black-box VI that bypasses the difficulties of stochastic gradient ascent, including the task of selecting step-sizes.
no code implementations • pproximateinference AABI Symposium 2022 • Javier Burroni, Kenta Takatsu, Justin Domke, Daniel Sheldon
We propose the use of U-statistics to reduce variance for gradient estimation in importance-weighted variational inference.
1 code implementation • 1 Feb 2023 • Jinlin Lai, Javier Burroni, Hui Guan, Daniel Sheldon
Hamiltonian Monte Carlo (HMC) is a powerful algorithm to sample latent variables from Bayesian models.
no code implementations • 25 Mar 2019 • Zenna Tavares, Xin Zhang, Edgar Minaysan, Javier Burroni, Rajesh Ranganath, Armando Solar Lezama
The need to condition distributional properties such as expectation, variance, and entropy arises in algorithmic fairness, model simplification, robustness and many other areas.
no code implementations • 16 Jan 2019 • Zenna Tavares, Javier Burroni, Edgar Minaysan, Armando Solar Lezama, Rajesh Ranganath
We develop a likelihood free inference procedure for conditioning a probabilistic model on a predicate.
1 code implementation • 30 Sep 2018 • Guillaume Baudart, Javier Burroni, Martin Hirzel, Louis Mandel, Avraham Shinnar
We use our compilation scheme to build two new backends for the Stanc3 compiler targeting Pyro and NumPyro.
no code implementations • 1 Aug 2018 • Jorge Brea, Javier Burroni, Carlos Sarraute
Over the past decade, mobile phones have become prevalent in all parts of the world, across all demographic backgrounds.