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Mansinghka, Vikash
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1

Visual object detection biases escape trajectories followin..:

Zwaka, Hanna ; McGinnis, Olivia J. ; Pflitsch, Paula...
Current Biology.  32 (2022)  23 - p. 5116-5125.e3 , 2022
Link: https://doi.org/10.1016/..
 
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2

A probabilistic model of cross-categorization:

Shafto, Patrick ; Kemp, Charles ; Mansinghka, Vikash.
Cognition.  120 (2011)  1 - p. 1-25 , 2011
Link: https://doi.org/10.1016/..
 
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3

GenSQL: A Probabilistic Programming System for Querying Gen..:

Huot, Mathieu ; Ghavami, Matin ; Lew, Alexander K....
Proceedings of the ACM on Programming Languages.  8 (2024)  PLDI - p. 790-815 , 2024
Link: https://doi.org/10.1145/..
 
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4

Probabilistic Programming with Programmable Variational Inf..:

Becker, McCoy R. ; Lew, Alexander K. ; Wang, Xiaoyan...
Proceedings of the ACM on Programming Languages.  8 (2024)  PLDI - p. 2123-2147 , 2024
Link: https://doi.org/10.1145/..
 
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5

Brain-wide representations of behavior spanning multiple ti..:

Atanas, Adam A. ; Kim, Jungsoo ; Wang, Ziyu...
Cell.  186 (2023)  19 - p. 4134-4151.e31 , 2023
Link: https://doi.org/10.1016/..
 
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6

ADEV: Sound Automatic Differentiation of Expected Values of..:

Lew, Alexander K. ; Huot, Mathieu ; Staton, Sam.
Proceedings of the ACM on Programming Languages.  7 (2023)  POPL - p. 121-153 , 2023
Link: https://doi.org/10.1145/..
 
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7

Optimal approximate sampling from discrete probability dist..:

Saad, Feras A. ; Freer, Cameron E. ; Rinard, Martin C..
Proceedings of the ACM on Programming Languages.  4 (2019)  POPL - p. 1-31 , 2019
Link: https://doi.org/10.1145/..
 
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8

Elements of a stochastic 3D prediction engine in larval zeb..:

Bolton, Andrew D ; Haesemeyer, Martin ; Jordi, Josua...
eLife.  8 (2019)  - p. , 2019
Link: https://doi.org/10.7554/..
 
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9

Bayesian synthesis of probabilistic programs for automatic ..:

Saad, Feras A. ; Cusumano-Towner, Marco F. ; Schaechtle, Ulrich..
Proceedings of the ACM on Programming Languages.  3 (2019)  POPL - p. 1-32 , 2019
Link: https://dl.acm.org/doi/1..
 
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10

Trace types and denotational semantics for sound programmab..:

Lew, Alexander K. ; Cusumano-Towner, Marco F. ; Sherman, Benjamin..
Proceedings of the ACM on Programming Languages.  4 (2019)  POPL - p. 1-32 , 2019
Link: https://doi.org/10.1145/..
 
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11

Bayesian synthesis of probabilistic programs for automatic ..:

Saad, Feras A. ; Cusumano-Towner, Marco F. ; Schaechtle, Ulrich..
Proceedings of the ACM on Programming Languages.  3 (2019)  POPL - p. 1-32 , 2019
Link: https://doi.org/10.1145/..
 
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12

Optimal approximate sampling from discrete probability dist..:

Saad, Feras A. ; Freer, Cameron E. ; Rinard, Martin C..
Proceedings of the ACM on Programming Languages.  4 (2019)  POPL - p. 1-31 , 2019
Link: https://dl.acm.org/doi/1..
 
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13

Trace types and denotational semantics for sound programmab..:

Lew, Alexander K. ; Cusumano-Towner, Marco F. ; Sherman, Benjamin..
Proceedings of the ACM on Programming Languages.  4 (2019)  POPL - p. 1-32 , 2019
Link: https://dl.acm.org/doi/1..
 
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14

Incremental inference for probabilistic programs:

Cusumano-Towner, Marco ; Bichsel, Benjamin ; Gehr, Timon..
ACM SIGPLAN Notices.  53 (2018)  4 - p. 571-585 , 2018
Link: https://doi.org/10.1145/..
 
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15

Probabilistic programming with programmable inference:

Mansinghka, Vikash K. ; Schaechtle, Ulrich ; Handa, Shivam...
ACM SIGPLAN Notices.  53 (2018)  4 - p. 603-616 , 2018
Link: https://doi.org/10.1145/..
 
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