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ORCIDMarco F. Cusumano-Towner
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- affiliation (PhD 2020): Massachusetts Institute of Technology (MIT), EECS, Cambridge, MA, USA
- affiliation: Stanford University, Department of Computer Science, CA, USA
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2020 – today
- 2026
[i13]Aleksei Petrenko, Ben Lipkin, Kevin Chen, Erik Wijmans, Marco F. Cusumano-Towner, Raja Giryes, Philipp Krähenbühl:
Entropy-Preserving Reinforcement Learning. CoRR abs/2603.11682 (2026)- 2025
- [c10]Marco Francis Cusumano-Towner, David Hafner, Alexander Hertzberg, Brody Huval, Aleksei Petrenko, Eugene Vinitsky, Erik Wijmans, Taylor W. Killian, Stuart Bowers, Ozan Sener, Philipp Krähenbühl, Vladlen Koltun:
Robust Autonomy Emerges from Self-Play. ICML 2025 - [i12]Kevin Chen, Marco F. Cusumano-Towner, Brody Huval, Aleksei Petrenko, Jackson Hamburger, Vladlen Koltun, Philipp Krähenbühl:
Reinforcement Learning for Long-Horizon Interactive LLM Agents. CoRR abs/2502.01600 (2025) - [i11]Marco F. Cusumano-Towner, David Hafner, Alexander Hertzberg, Brody Huval, Aleksei Petrenko, Eugene Vinitsky
, Erik Wijmans, Taylor W. Killian, Stuart Bowers, Ozan Sener, Philipp Krähenbühl, Vladlen Koltun:
Robust Autonomy Emerges from Self-Play. CoRR abs/2502.03349 (2025) - 2022
- [c9]Feras Saad, Marco F. Cusumano-Towner, Vikash Mansinghka:
Estimators of Entropy and Information via Inference in Probabilistic Models. AISTATS 2022: 5604-5621 - [c8]Alexander K. Lew, Marco F. Cusumano-Towner, Vikash K. Mansinghka:
Recursive Monte Carlo and variational inference with auxiliary variables. UAI 2022: 1096-1106 - [i10]Feras A. Saad, Marco F. Cusumano-Towner, Vikash K. Mansinghka:
Estimators of Entropy and Information via Inference in Probabilistic Models. CoRR abs/2202.12363 (2022) - [i9]Alexander K. Lew, Marco F. Cusumano-Towner, Vikash K. Mansinghka:
Recursive Monte Carlo and Variational Inference with Auxiliary Variables. CoRR abs/2203.02836 (2022) - 2021
- [c7]Nishad Gothoskar, Marco F. Cusumano-Towner, Ben Zinberg, Matin Ghavamizadeh, Falk Pollok, Austin Garrett, Josh Tenenbaum, Dan Gutfreund, Vikash K. Mansinghka:
3DP3: 3D Scene Perception via Probabilistic Programming. NeurIPS 2021: 9600-9612 - [i8]Nishad Gothoskar, Marco F. Cusumano-Towner, Ben Zinberg, Matin Ghavamizadeh, Falk Pollok, Austin Garrett, Joshua B. Tenenbaum, Dan Gutfreund, Vikash K. Mansinghka:
3DP3: 3D Scene Perception via Probabilistic Programming. CoRR abs/2111.00312 (2021) - 2020
- [j3]Alexander K. Lew, Marco F. Cusumano-Towner, Benjamin Sherman, Michael Carbin, Vikash K. Mansinghka:
Trace types and denotational semantics for sound programmable inference in probabilistic languages. Proc. ACM Program. Lang. 4(POPL): 19:1-19:32 (2020)
2010 – 2019
- 2019
- [j2]Feras A. Saad, Marco F. Cusumano-Towner, Ulrich Schaechtle, Martin C. Rinard, Vikash K. Mansinghka:
Bayesian synthesis of probabilistic programs for automatic data modeling. Proc. ACM Program. Lang. 3(POPL): 37:1-37:32 (2019) - [c6]Marco F. Cusumano-Towner, Feras A. Saad, Alexander K. Lew, Vikash K. Mansinghka:
Gen: a general-purpose probabilistic programming system with programmable inference. PLDI 2019: 221-236 - [i7]Feras A. Saad, Marco F. Cusumano-Towner, Ulrich Schaechtle, Martin C. Rinard, Vikash K. Mansinghka:
Bayesian Synthesis of Probabilistic Programs for Automatic Data Modeling. CoRR abs/1907.06249 (2019) - 2018
- [c5]Marco F. Cusumano-Towner, Vikash K. Mansinghka:
A design proposal for Gen: probabilistic programming with fast custom inference via code generation. MAPL@PLDI 2018: 52-57 - [c4]Marco F. Cusumano-Towner, Benjamin Bichsel, Timon Gehr, Martin T. Vechev, Vikash K. Mansinghka:
Incremental inference for probabilistic programs. PLDI 2018: 571-585 - [i6]Marco F. Cusumano-Towner, Vikash K. Mansinghka:
Using probabilistic programs as proposals. CoRR abs/1801.03612 (2018) - 2017
- [c3]Marco F. Cusumano-Towner, Vikash K. Mansinghka:
AIDE: An algorithm for measuring the accuracy of probabilistic inference algorithms. NIPS 2017: 3000-3010 - [i5]Marco F. Cusumano-Towner, Alexey Radul, David Wingate, Vikash K. Mansinghka:
Probabilistic programs for inferring the goals of autonomous agents. CoRR abs/1704.04977 (2017) - [i4]Marco F. Cusumano-Towner, Vikash K. Mansinghka:
AIDE: An algorithm for measuring the accuracy of probabilistic inference algorithms. CoRR abs/1705.07224 (2017) - 2016
- [i3]Marco F. Cusumano-Towner, Vikash K. Mansinghka:
Quantifying the probable approximation error of probabilistic inference programs. CoRR abs/1606.00068 (2016) - [i2]Marco F. Cusumano-Towner, Vikash K. Mansinghka:
Measuring the non-asymptotic convergence of sequential Monte Carlo samplers using probabilistic programming. CoRR abs/1612.02161 (2016) - [i1]Marco F. Cusumano-Towner, Vikash K. Mansinghka:
Encapsulating models and approximate inference programs in probabilistic modules. CoRR abs/1612.04759 (2016) - 2013
- [j1]Marco F. Cusumano-Towner, Daniel Y. Li, Shanshan Tuo, Gomathi Krishnan, David M. Maslove:
A social network of hospital acquired infection built from electronic medical record data. J. Am. Medical Informatics Assoc. 20(3): 427-434 (2013) - 2011
- [c2]Marco F. Cusumano-Towner, Arjun Singh, Stephen Miller, James F. O'Brien, Pieter Abbeel:
Bringing clothing into desired configurations with limited perception. ICRA 2011: 3893-3900 - 2010
- [c1]Jeremy Maitin-Shepard, Marco F. Cusumano-Towner, Jinna Lei, Pieter Abbeel:
Cloth grasp point detection based on multiple-view geometric cues with application to robotic towel folding. ICRA 2010: 2308-2315
Coauthor Index
aka: Vikash K. Mansinghka
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last updated on 2026-04-12 23:42 CEST by the dblp team
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