Yura Perov
Yura Perov
Babylon Health, London, UK
Verified email at - Homepage
Cited by
Cited by
Venture: a higher-order probabilistic programming platform with programmable inference
V Mansinghka, D Selsam, Y Perov
arXiv preprint arXiv:1404.0099, 2014
Approximate bayesian image interpretation using generative probabilistic graphics programs
VK Mansinghka, TD Kulkarni, YN Perov, J Tenenbaum
Advances in Neural Information Processing Systems 26, 2013
A comparative study of artificial intelligence and human doctors for the purpose of triage and diagnosis
S Razzaki, A Baker, Y Perov, K Middleton, J Baxter, D Mullarkey, ...
arXiv preprint arXiv:1806.10698, 2018
A universal marginalizer for amortized inference in generative models
L Douglas, I Zarov, K Gourgoulias, C Lucas, C Hart, A Baker, M Sahani, ...
arXiv preprint arXiv:1711.00695, 2017
Gait optimization for roombots modular robots—Matching simulation and reality
R Moeckel, YN Perov, AT Nguyen, M Vespignani, S Bonardi, S Pouya, ...
2013 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2013
A comparison of artificial intelligence and human doctors for the purpose of triage and diagnosis
A Baker, Y Perov, K Middleton, J Baxter, D Mullarkey, D Sangar, M Butt, ...
Frontiers in artificial intelligence 3, 543405, 2020
Multiverse: causal reasoning using importance sampling in probabilistic programming
Y Perov, L Graham, K Gourgoulias, J Richens, C Lee, A Baker, S Johri
Symposium on advances in approximate bayesian inference, 1-36, 2020
Automatic sampler discovery via probabilistic programming and approximate bayesian computation
Y Perov, F Wood
International Conference on Artificial General Intelligence, 262-273, 2016
Learning probabilistic programs
YN Perov, FD Wood
arXiv preprint arXiv:1407.2646, 2014
Data-driven sequential Monte Carlo in probabilistic programming
YN Perov, TA Le, F Wood
arXiv preprint arXiv:1512.04387, 2015
Anh The Nguyen, Massimo Vespignani, Stephane Bonardi, Soha Pouya, Alexander Spröwitz, Jesse van den Kieboom, Frederic Wilhelm, and Auke Jan Ijspeert. Gait optimization for …
R Moeckel, NP Yura
Proceedings of the 2013 IEEE/RSJ International Conference on Intelligent …, 2013
Computing engine, software, system and method
F Wood, M Wu, Y Perov, H Yang
US Patent App. 15/465,131, 2017
Applications of Probabilistic Programming (Master's thesis, 2015)
YN Perov
arXiv preprint arXiv:1606.00075, 2016
Learning medical triage from clinicians using deep q-learning
A Buchard, B Bouvier, G Prando, R Beard, M Livieratos, D Busbridge, ...
arXiv preprint arXiv:2003.12828, 2020
Nonparametric Bayesian models for unsupervised activity recognition and tracking
N Dhir, Y Perov, F Wood
2016 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2016
Applying Artificial Intelligence Methods for the Estimation of Disease Incidence: The Utility of Language Models
Y Zhang, R Walecki, JR Winter, FJS Bragman, S Lourenco, C Hart, ...
Frontiers in digital health 2, 569261, 2020
Copy, paste, infer: a robust analysis of twin networks for counterfactual inference
L Graham, CM Lee, Y Perov
NeurIPS19 CausalML workshop, 2019
Universal marginalizer for amortised inference and embedding of generative models
R Walecki, A Buchard, K Gourgoulias, C Hart, M Lomeli, AKW Navarro, ...
arXiv preprint arXiv:1811.04727, 2018
Spreadsheet probabilistic programming
M Wu, Y Perov, F Wood, H Yang
arXiv preprint arXiv:1606.04216, 2016
Applications of probabilistic programming
Y Perov
University of Oxford, 2015
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