| 2024 | UAI | Sample Average Approximation for Black-Box Variational Inference. | Javier Burroni, Justin Domke, Daniel Sheldon |
| 2023 | ICML | Automatically marginalized MCMC in probabilistic programming. | Jinlin Lai, Javier Burroni, Hui Guan, Daniel Sheldon |
| 2021 | PLDI | Compiling Stan to generative probabilistic languages and extension to deep probabilistic programming. | Guillaume Baudart, Javier Burroni, Martin Hirzel, Louis Mandel, Avraham Shinnar |
| 2021 | UAI | Min/max stability and box distributions. | Michael Boratko, Javier Burroni, Shib Sankar Dasgupta, Andrew McCallum |
| 2019 | ICML | Predicate Exchange: Inference with Declarative Knowledge. | Zenna Tavares, Javier Burroni, Edgar Minasyan, Armando Solar-Lezama, Rajesh Ranganath |
| 2019 | UAI | Object Conditioning for Causal Inference. | David D. Jensen, Javier Burroni, Matthew J. Rattigan |
| 2017 | DLS | Garbage collection and efficiency in dynamic metacircular runtimes: an experience report. | Javier Pims, Javier Burroni, Jean-Baptiste Arnaud, Stefan Marr |
| 2014 | KDD | Harnessing Mobile Phone Social Network Topology to Infer Users Demographic Attributes. | Jorge Brea, Javier Burroni, Martin Minnoni, Carlos Sarraute |