Vikash K. Mansinghka
Vikash K. Mansinghka
MIT, Probabilistic Computing Project
Verified email at mit.edu - Homepage
Title
Cited by
Cited by
Year
Church: a language for generative models
N Goodman, V Mansinghka, DM Roy, K Bonawitz, JB Tenenbaum
arXiv preprint arXiv:1206.3255, 2012
8222012
A new approach to probabilistic programming inference
F Wood, JW Meent, V Mansinghka
Artificial Intelligence and Statistics, 1024-1032, 2014
3062014
Venture: a higher-order probabilistic programming platform with programmable inference
V Mansinghka, D Selsam, Y Perov
arXiv preprint arXiv:1404.0099, 2014
1892014
Picture: A probabilistic programming language for scene perception
TD Kulkarni, P Kohli, JB Tenenbaum, V Mansinghka
Proceedings of the ieee conference on computer vision and pattern …, 2015
1822015
Reconciling intuitive physics and Newtonian mechanics for colliding objects.
AN Sanborn, VK Mansinghka, TL Griffiths
Psychological review 120 (2), 411, 2013
1482013
Intuitive theories of mind: A rational approach to false belief
ND Goodman, CL Baker, EB Bonawitz, VK Mansinghka, A Gopnik, ...
Proceedings of the twenty-eighth annual conference of the cognitive science …, 2006
1052006
Approximate bayesian image interpretation using generative probabilistic graphics programs
VK Mansinghka, TD Kulkarni, YN Perov, JB Tenenbaum
arXiv preprint arXiv:1307.0060, 2013
972013
Structured priors for structure learning
V Mansinghka, C Kemp, T Griffiths, J Tenenbaum
arXiv preprint arXiv:1206.6852, 2012
852012
Learning annotated hierarchies from relational data
DM Roy, C Kemp, V Mansinghka, J B Tenenbaum
Carnegie Mellon University, 2007
692007
Gen: A general-purpose probabilistic programming system with programmable inference
MF Cusumano-Towner, FA Saad, A Lew, VK and Mansinghka
Technical Report MIT-CSAIL-TR-2018-020, Computer Science and Artificial …, 2019
632019
Natively probabilistic computation
VK Mansinghka
Massachusetts Institute of Technology, Department of Brain and Cognitive …, 2009
592009
Natively probabilistic computation
VK Mansinghka
Massachusetts Institute of Technology, Department of Brain and Cognitive …, 2009
592009
A probabilistic model of cross-categorization
P Shafto, C Kemp, V Mansinghka, JB Tenenbaum
Cognition 120 (1), 1-25, 2011
552011
Learning cross-cutting systems of categories
P Shafto, C Kemp, V Mansinghka, M Gordon, JB Tenenbaum
Proceedings of the 28th annual conference of the Cognitive Science Society …, 2006
392006
Combinational stochastic logic
VK Mansinghka, EM Jonas
US Patent 8,352,384, 2013
302013
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
272019
Crosscat: A fully bayesian nonparametric method for analyzing heterogeneous, high dimensional data
V Mansinghka, P Shafto, E Jonas, C Petschulat, M Gasner, ...
MIT Press, 2016
272016
Stochastic digital circuits for probabilistic inference
VK Mansinghka, EM Jonas, JB Tenenbaum
Massachussets Institute of Technology, Technical Report MITCSAIL-TR 2069, 2008
262008
BayesDB: A probabilistic programming system for querying the probable implications of data
V Mansinghka, R Tibbetts, J Baxter, P Shafto, B Eaves
arXiv preprint arXiv:1512.05006, 2015
252015
Particle Gibbs with ancestor sampling for probabilistic programs
JW Meent, H Yang, V Mansinghka, F Wood
Artificial Intelligence and Statistics, 986-994, 2015
242015
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