| Denotational validation of higher-order Bayesian inference A Ścibior, O Kammar, M Vákár, S Staton, H Yang, Y Cai, K Ostermann, ... Proceedings of the ACM on Programming Languages 2 (POPL), 1-29, 2017 | 83 | 2017 |
| Practical probabilistic programming with monads A Ścibior, Z Ghahramani, AD Gordon Proceedings of the 2015 ACM SIGPLAN Symposium on Haskell, 165-176, 2015 | 76 | 2015 |
| Functional programming for modular Bayesian inference A Ścibior, O Kammar, Z Ghahramani Proceedings of the ACM on Programming Languages 2 (ICFP), 1-29, 2018 | 39 | 2018 |
| 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 | 34 | 2021 |
| Robust asymmetric learning in pomdps A Warrington, JW Lavington, A Scibior, M Schmidt, F Wood International Conference on Machine Learning, 11013-11023, 2021 | 28 | 2021 |
| 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 | 18 | 2022 |
| Differentiable particle filtering without modifying the forward pass A Ścibior, F Wood arXiv preprint arXiv:2106.10314, 2021 | 16 | 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 | 14 | 2019 |
| 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 | 11 | 2018 |
| 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 |
| 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 | 8 | 2016 |
| Conditional permutation invariant flows B Zwartsenberg, A Ścibior, M Niedoba, V Lioutas, Y Liu, J Sefas, S Dabiri, ... arXiv preprint arXiv:2206.09021, 2022 | 7 | 2022 |
| 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 | 6 | 2022 |
| Titrated: Learned human driving behavior without infractions via amortized inference V Lioutas, A Scibior, F Wood Transactions on Machine Learning Research, 2022 | 6 | 2022 |
| 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 |
| 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 | 5 | 2019 |
| Critic sequential monte carlo V Lioutas, JW Lavington, J Sefas, M Niedoba, Y Liu, B Zwartsenberg, ... arXiv preprint arXiv:2205.15460, 2022 | 4 | 2022 |
| Neurips 2022 competition: Driving smarts A Rasouli, R Goebel, ME Taylor, I Kotseruba, S Alizadeh, T Yang, ... arXiv preprint arXiv:2211.07545, 2022 | 3 | 2022 |
| The Turing language for probabilistic programming H Ge, K Xu, A Scibior, Z Ghahramani Artificial Intelligence and Statistics, 2018 | 3 | 2018 |
Frank WoodUniversity of British Columbia在 cs.ubc.ca 的电子邮件经过验证
