Adam Ścibior
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Practical probabilistic programming with monads
A Ścibior, Z Ghahramani, AD Gordon
Proceedings of the 2015 ACM SIGPLAN Symposium on Haskell, 165-176, 2015
Denotational validation of higher-order Bayesian inference
A Ścibior, O Kammar, M Vákár, S Staton, H Yang, Y Cai, K Ostermann, ...
arXiv preprint arXiv:1711.03219, 2017
Functional programming for modular Bayesian inference
A Ścibior, O Kammar, Z Ghahramani
Proceedings of the ACM on Programming Languages 2 (ICFP), 1-29, 2018
Planning as inference in epidemiological models
F Wood, A Warrington, S Naderiparizi, C Weilbach, V Masrani, W Harvey, ...
arXiv preprint arXiv:2003.13221, 2020
Fabular: Regression formulas as probabilistic programming
J Borgström, AD Gordon, L Ouyang, C Russo, A Ścibior, M Szymczak
Proceedings of the 43rd Annual ACM SIGPLAN-SIGACT Symposium on Principles of …, 2016
Consistent kernel mean estimation for functions of random variables
CJ Simon-Gabriel, A Scibior, IO Tolstikhin, B Schölkopf
Advances in Neural Information Processing Systems 29, 1732-1740, 2016
Deep probabilistic surrogate networks for universal simulator approximation
A Munk, A Ścibior, AG Baydin, A Stewart, G Fernlund, A Poursartip, ...
arXiv preprint arXiv:1910.11950, 2019
Robust asymmetric learning in pomdps
A Warrington, JW Lavington, A Scibior, M Schmidt, F Wood
International Conference on Machine Learning, 11013-11023, 2021
The semantic structure of quasi-Borel spaces
C Heunen, O Kammar, S Staton, S Moss, M Vákár, A Ścibior, H Yang
PPS18, 2018
The Turing language for probabilistic programming
H Ge, K Xu, A Scibior, Z Ghahramani
Artificial Intelligence and Statistics, 2018
Modular construction of Bayesian inference algorithms
A Scibior, Z Ghahramani
NIPS Workshop on Advances in Approximate Bayesian Inference, 2016
Imagining The Road Ahead: Multi-Agent Trajectory Prediction via Differentiable Simulation
A Scibior, V Lioutas, D Reda, P Bateni, F Wood
arXiv preprint arXiv:2104.11212, 2021
Semi-supervised sequential generative models
M Teng, TA Le, A Scibior, F Wood
arXiv preprint arXiv:2007.00155, 2020
Amortized rejection sampling in universal probabilistic programming
S Naderiparizi, A Ścibior, A Munk, M Ghadiri, AG Baydin, B Gram-Hansen, ...
arXiv preprint arXiv:1910.09056, 2019
Efficient Bayesian inference for nested simulators
B Gram-Hansen, CS de Witt, R Zinkov, S Naderiparizi, A Scibior, A Munk, ...
Strongly typed tracing of probabilistic programs
A Ścibior, M Thomas
LAFI, 2019
Building inference algorithms from monad transformers
A Scibior, Y Cai, K Ostermann, Z Ghahramani
Formally justified and modular Bayesian inference for probabilistic programs
AM Ścibior
University of Cambridge, 2019
Imitation learning of factored multi-agent reactive models
M Teng, TA Le, A Scibior, F Wood
arXiv preprint arXiv:1903.04714, 2019
Effects in Bayesian inference
A Scibior, O Kammar
Workshop on Higher-Order Programming with Effects (HOPE), 2015
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