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Vikash K. Mansinghka

Publication record assembled from the DBLP archive of ranked conferences.

Papers indexed

16

Venues

7

Active years

2006–2023

Best venue rank

A*

Where they publish

Papers

16 indexed papers, newest first.

YearVenueTitleAuthors
2023AISTATSProbNeRF: Uncertainty-Aware Inference of 3D Shapes from 2D Images.Matthew D. Hoffman, Tuan Anh Le, Pavel Sountsov, Christopher Suter, Ben Lee, Vikash K. Mansinghka, Rif A. Saurous
2023AISTATSSMCP3: Sequential Monte Carlo with Probabilistic Program Proposals.Alexander K. Lew, George Matheos, Tan Zhi-Xuan, Matin Ghavamizadeh, Nishad Gothoskar, Stuart Russell, Vikash K. Mansinghka
2023ICCV3D Neural Embedding Likelihood: Probabilistic Inverse Graphics for Robust 6D Pose Estimation.Guangyao Zhou, Nishad Gothoskar, Lirui Wang, Joshua B. Tenenbaum, Dan Gutfreund, Miguel Lzaro-Gredilla, Dileep George, Vikash K. Mansinghka
2023LICSωPAP Spaces: Reasoning Denotationally About Higher-Order, Recursive Probabilistic and Differentiable Programs.Mathieu Huot, Alexander K. Lew, Vikash K. Mansinghka, Sam Staton
2022ICRADURableVS: Data-efficient Unsupervised Recalibrating Visual Servoing via online learning in a structured generative model.Nishad Gothoskar, Miguel Lzaro-Gredilla, Yasemin Bekiroglu, Abhishek Agarwal, Joshua B. Tenenbaum, Vikash K. Mansinghka, Dileep George
2022UAIRecursive Monte Carlo and variational inference with auxiliary variables.Alexander K. Lew, Marco F. Cusumano-Towner, Vikash K. Mansinghka
2021PLDISPPL: probabilistic programming with fast exact symbolic inference.Feras A. Saad, Martin C. Rinard, Vikash K. Mansinghka
2021UAIHierarchical infinite relational model.Feras A. Saad, Vikash K. Mansinghka
2019AISTATSA Family of Exact Goodness-of-Fit Tests for High-Dimensional Discrete Distributions.Feras A. Saad, Cameron E. Freer, Nathanael L. Ackerman, Vikash K. Mansinghka
2019PLDIGen: a general-purpose probabilistic programming system with programmable inference.Marco F. Cusumano-Towner, Feras A. Saad, Alexander K. Lew, Vikash K. Mansinghka
2018PLDIA design proposal for Gen: probabilistic programming with fast custom inference via code generation.Marco F. Cusumano-Towner, Vikash K. Mansinghka
2018PLDIIncremental inference for probabilistic programs.Marco F. Cusumano-Towner, Benjamin Bichsel, Timon Gehr, Martin T. Vechev, Vikash K. Mansinghka
2018PLDIProbabilistic programming with programmable inference.Vikash K. Mansinghka, Ulrich Schaechtle, Shivam Handa, Alexey Radul, Yutian Chen, Martin C. Rinard
2013ACSSCMarkov chain algorithms: A template for building future robust low power systems.Biplab Deka, Alex A. Birklykke, Henry Duwe, Vikash K. Mansinghka, Rakesh Kumar
2008UAIChurch: a language for generative models.Noah D. Goodman, Vikash K. Mansinghka, Daniel M. Roy, Kallista A. Bonawitz, Joshua B. Tenenbaum
2006UAIStructured Priors for Structure Learning.Vikash K. Mansinghka, Charles Kemp, Thomas L. Griffiths, Joshua B. Tenenbaum