Marco F. Cusumano-Towner

According to our database, Marco F. Cusumano-Towner authored at least 17 papers between 2010 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

Recursive Monte Carlo and variational inference with auxiliary variables.

Alexander K. Lew, Marco F. Cusumano-Towner, Vikash K. Mansinghka

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Estimators of Entropy and Information via Inference in Probabilistic Models.

Feras Saad, Marco F. Cusumano-Towner, Vikash Mansinghka

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

3DP3: 3D Scene Perception via Probabilistic Programming.

Nishad Gothoskar, Marco F. Cusumano-Towner, Ben Zinberg, Matin Ghavamizadeh, Falk Pollok, Austin Garrett, Josh Tenenbaum, Dan Gutfreund, Vikash K. Mansinghka

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Trace types and denotational semantics for sound programmable inference in probabilistic languages.

Alexander K. Lew, Marco F. Cusumano-Towner, Benjamin Sherman, Michael Carbin, Vikash K. Mansinghka

Proc. ACM Program. Lang., 2020

2019

Bayesian synthesis of probabilistic programs for automatic data modeling.

Feras A. Saad, Marco F. Cusumano-Towner, Ulrich Schaechtle, Martin C. Rinard, Vikash K. Mansinghka

Proc. ACM Program. Lang., 2019

Gen: a general-purpose probabilistic programming system with programmable inference.

Marco F. Cusumano-Towner, Feras A. Saad, Alexander K. Lew, Vikash K. Mansinghka

Proceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation, 2019

2018

Using probabilistic programs as proposals.

Marco F. Cusumano-Towner, Vikash K. Mansinghka

CoRR, 2018

Incremental inference for probabilistic programs.

Marco F. Cusumano-Towner, Benjamin Bichsel, Timon Gehr, Martin T. Vechev, Vikash K. Mansinghka

Proceedings of the 39th ACM SIGPLAN Conference on Programming Language Design and Implementation, 2018

A design proposal for Gen: probabilistic programming with fast custom inference via code generation.

Marco F. Cusumano-Towner, Vikash K. Mansinghka

Proceedings of the 2nd ACM SIGPLAN International Workshop on Machine Learning and Programming Languages, 2018

2017

Probabilistic programs for inferring the goals of autonomous agents.

Marco F. Cusumano-Towner, Alexey Radul, David Wingate, Vikash K. Mansinghka

CoRR, 2017

AIDE: An algorithm for measuring the accuracy of probabilistic inference algorithms.

Marco F. Cusumano-Towner, Vikash K. Mansinghka

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

Encapsulating models and approximate inference programs in probabilistic modules.

Marco F. Cusumano-Towner, Vikash K. Mansinghka

CoRR, 2016

Measuring the non-asymptotic convergence of sequential Monte Carlo samplers using probabilistic programming.

Marco F. Cusumano-Towner, Vikash K. Mansinghka

CoRR, 2016

Quantifying the probable approximation error of probabilistic inference programs.

Marco F. Cusumano-Towner, Vikash K. Mansinghka

CoRR, 2016

2013

A social network of hospital acquired infection built from electronic medical record data.

Marco F. Cusumano-Towner, Daniel Y. Li, Shanshan Tuo, Gomathi Krishnan, David M. Maslove

J. Am. Medical Informatics Assoc., 2013

2011

Bringing clothing into desired configurations with limited perception.

Marco F. Cusumano-Towner, Arjun Singh, Stephen Miller, James F. O'Brien, Pieter Abbeel

Proceedings of the IEEE International Conference on Robotics and Automation, 2011

2010

Cloth grasp point detection based on multiple-view geometric cues with application to robotic towel folding.

Jeremy Maitin-Shepard, Marco F. Cusumano-Towner, Jinna Lei, Pieter Abbeel

Proceedings of the IEEE International Conference on Robotics and Automation, 2010