| Cloth grasp point detection based on multiple-view geometric cues with application to robotic towel folding J Maitin-Shepard, M Cusumano-Towner, J Lei, P Abbeel 2010 IEEE International Conference on Robotics and Automation, 2308-2315, 2010 | 606 | 2010 |
| Gen: a general-purpose probabilistic programming system with programmable inference MF Cusumano-Towner, FA Saad, AK Lew, VK Mansinghka Proceedings of the 40th acm sigplan conference on programming language …, 2019 | 237 | 2019 |
| Bringing clothing into desired configurations with limited perception M Cusumano-Towner, A Singh, S Miller, JF O'Brien, P Abbeel 2011 IEEE international conference on robotics and automation, 3893-3900, 2011 | 193 | 2011 |
| Bayesian synthesis of probabilistic programs for automatic data modeling FA Saad, MF Cusumano-Towner, U Schaechtle, MC Rinard, ... Proceedings of the ACM on Programming Languages 3 (POPL), 1-32, 2019 | 73 | 2019 |
| 3DP3: 3D scene perception via probabilistic programming N Gothoskar, M Cusumano-Towner, B Zinberg, M Ghavamizadeh, ... Advances in Neural Information Processing Systems 34, 9600-9612, 2021 | 57 | 2021 |
| Trace types and denotational semantics for sound programmable inference in probabilistic languages AK Lew, MF Cusumano-Towner, B Sherman, M Carbin, VK Mansinghka Proceedings of the ACM on Programming Languages 4 (POPL), 1-32, 2019 | 52 | 2019 |
| A social network of hospital acquired infection built from electronic medical record data M Cusumano-Towner, DY Li, S Tuo, G Krishnan, DM Maslove Journal of the American Medical Informatics Association 20 (3), 427-434, 2013 | 48 | 2013 |
| AIDE: An algorithm for measuring the accuracy of probabilistic inference algorithms M Cusumano-Towner, VK Mansinghka Advances in Neural Information Processing Systems 30, 2017 | 31 | 2017 |
| Probabilistic programs for inferring the goals of autonomous agents MF Cusumano-Towner, A Radul, D Wingate, VK Mansinghka arXiv preprint arXiv:1704.04977, 2017 | 22 | 2017 |
| Automating involutive MCMC using probabilistic and differentiable programming M Cusumano-Towner, AK Lew, VK Mansinghka arXiv preprint arXiv:2007.09871, 2020 | 20 | 2020 |
| Incremental inference for probabilistic programs M Cusumano-Towner, B Bichsel, T Gehr, M Vechev, VK Mansinghka Proceedings of the 39th ACM SIGPLAN Conference on Programming Language …, 2018 | 20 | 2018 |
| Using probabilistic programs as proposals MF Cusumano-Towner, VK Mansinghka arXiv preprint arXiv:1801.03612, 2018 | 16 | 2018 |
| Recursive Monte Carlo and variational inference with auxiliary variables AK Lew, M Cusumano-Towner, VK Mansinghka Uncertainty in artificial intelligence, 1096-1106, 2022 | 13 | 2022 |
| A design proposal for Gen: Probabilistic programming with fast custom inference via code generation M Cusumano-Towner, VK Mansinghka Proceedings of the 2nd ACM SIGPLAN International Workshop on Machine …, 2018 | 8 | 2018 |
| Structured differentiable models of 3d scenes via generative scene graphs B Zinberg, M Cusumano-Towner, KM Vikash Workshop on Perception as Generative Reasoning, NeurIPS, Submitted September, 2019 | 7 | 2019 |
| Gen: a high-level programming platform for probabilistic inference MF Cusumano-Towner Massachusetts Institute of Technology, 2020 | 5 | 2020 |
| Estimators of entropy and information via inference in probabilistic models F Saad, M Cusumano-Towner, V Mansinghka International Conference on Artificial Intelligence and Statistics, 5604-5621, 2022 | 4 | 2022 |
| Transforming worlds: Automated involutive MCMC for open-universe probabilistic models G Matheos, AK Lew, M Ghavamizadeh, S Russell, M Cusumano-Towner, ... Third Symposium on Advances in Approximate Bayesian Inference, 2020 | 4 | 2020 |
| Encapsulating models and approximate inference programs in probabilistic modules MF Cusumano-Towner, VK Mansinghka arXiv preprint arXiv:1612.04759, 2016 | 4 | 2016 |
| Quantifying the probable approximation error of probabilistic inference programs MF Cusumano-Towner, VK Mansinghka arXiv preprint arXiv:1606.00068, 2016 | 4 | 2016 |
Vikash K. MansinghkaMIT, Probabilistic Computing ProjectEmail verificata su mit.edu
