Adam Ścibior

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	All	Since 2018
Citations	294	260
h-index	8	8
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Frank WoodUniversity of British ColumbiaVerified email at cs.ubc.ca
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleVerified email at eng.cam.ac.uk
Ohad KammarUniversity of Edinburgh School of InformaticsVerified email at ed.ac.uk
Andrew D GordonMicrosoft Research and University of EdinburghVerified email at microsoft.com
Hongseok YangProfessor, School of Computing, KAISTVerified email at kaist.ac.kr
Chris HeunenUniversity of EdinburghVerified email at ed.ac.uk
Matthijs VákárAssistant Professor, Utrecht UniversityVerified email at uu.nl
Klaus OstermannProfessor of Computer Science, University of Tübingen, GermanyVerified email at uni-tuebingen.de
Atılım Güneş BaydinUniversity of OxfordVerified email at robots.ox.ac.uk
Andreas MunkPhD student, University of British ColumbiaVerified email at cs.ubc.ca
Andrew WarringtonPostdoc, Stanford UniversityVerified email at stanford.edu
Jonathan Wilder LavingtonPhD Student, University of British ColumbiaVerified email at cs.ubc.ca
Saeid NaderipariziPhD student, University of British ColumbiaVerified email at cs.ubc.ca
Vasileios LioutasPh.D. Student, University of British ColumbiaVerified email at cs.ubc.ca
William HarveyPhD student, University of British ColumbiaVerified email at cs.ubc.ca
Vaden MasraniUniversity of British ColumbiaVerified email at cs.ubc.ca
Boyan BeronovUniversity of British ColumbiaVerified email at cs.ubc.ca
S. Ali NasseriCanadian Space AgencyVerified email at asc-csa.gc.ca
Christian WeilbachPhD Candidate, University of British ColumbiaVerified email at cs.ubc.ca
John GrefenstetteProfessor of Health Policy and Management, University of PittsburghVerified email at pitt.edu

Adam Ścibior

University of British Columbia

Verified email at cs.ubc.ca - Homepage

Machine Learning Programming Languages


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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	71	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	69	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	32	2018
Planning as Inference in Epidemiological Dynamics Models F Wood, A Warrington, S Naderiparizi, C Weilbach, V Masrani, W Harvey, ... Frontiers in Artificial Intelligence 4, 550603, 2022	19	2022
Robust asymmetric learning in pomdps A Warrington, JW Lavington, A Scibior, M Schmidt, F Wood International Conference on Machine Learning, 11013-11023, 2021	17	2021
Imagining the road ahead: Multi-agent trajectory prediction via differentiable simulation A Ścibior, V Lioutas, D Reda, P Bateni, F Wood 2021 IEEE International Intelligent Transportation Systems Conference (ITSC …, 2021	14	2021
Deep probabilistic surrogate networks for universal simulator approximation A Munk, A Scibior, AG Baydin, A Stewart, G Fernlund, A Poursartip, ... arXiv preprint arXiv:1910.11950 25, 2019	9	2019
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, 2016	9	2016
The semantic structure of quasi-Borel spaces C Heunen, O Kammar, S Staton, S Moss, M Vákár, A Ścibior, H Yang PPS Workshop on Probabilistic Programming Semantics, 2018	8	2018
Differentiable particle filtering without modifying the forward pass A Ścibior, F Wood arXiv preprint arXiv:2106.10314, 2021	7	2021
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	7	2016
Amortized rejection sampling in universal probabilistic programming S Naderiparizi, A Scibior, A Munk, M Ghadiri, AG Baydin, ... International Conference on Artificial Intelligence and Statistics, 8392-8412, 2022	5	2022
Semi-supervised sequential generative models M Teng, TA Le, A Scibior, F Wood arXiv preprint arXiv:2007.00155, 2020	5	2020
Effects in Bayesian inference A Scibior, O Kammar Workshop on Higher-Order Programming with Effects (HOPE), 2015	4	2015
Probabilistic surrogate networks for simulators with unbounded randomness A Munk, B Zwartsenberg, A Ścibior, AGG Baydin, A Stewart, G Fernlund, ... Uncertainty in Artificial Intelligence, 1423-1433, 2022	3	2022
The Turing language for probabilistic programming H Ge, K Xu, A Scibior, Z Ghahramani The Turing language for probabilistic programming, 2016	3	2016
Modular construction of Bayesian inference algorithms A Scibior, Z Ghahramani NIPS Workshop on Advances in Approximate Bayesian Inference, 2016	3	2016
Efficient Bayesian inference for nested simulators B Gram-Hansen, CS de Witt, R Zinkov, S Naderiparizi, A Scibior, A Munk, ... Second Symposium on Advances in Approximate Bayesian Inference, 2019	2	2019
Formally justified and modular Bayesian inference for probabilistic programs AM Ścibior University of Cambridge, 2019	2	2019
Strongly typed tracing of probabilistic programs A Ścibior, M Thomas LAFI, 2019	2	2019

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