Gait optimization for roombots modular robots - Matching simulation and reality. - Rico Moeckel; Yura N. Perov; Anh The Nguyen; Massimo Vespignani; Stéphane Bonardi; Soha Pouya; Alexander Sproewitz; Jesse van den Kieboom; Frédéric Wilhelm; Auke Jan Ijspeert (IROS, 2013)

Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs. - Vikash K. Mansinghka; Tejas D. Kulkarni; Yura N. Perov; Joshua B. Tenenbaum (NIPS, 2013)

Venture: a higher-order probabilistic programming platform with programmable inference. - Vikash Mansinghka 001; Daniel Selsam; Yura N. Perov (CoRR, 2014)

Learning Probabilistic Programs. - Yura N. Perov; Frank D. Wood (CoRR, 2014)

Data-driven Sequential Monte Carlo in Probabilistic Programming. - Yura N. Perov; Tuan Anh Le 001; Frank D. Wood (CoRR, 2015)

Automatic Sampler Discovery via Probabilistic Programming and Approximate Bayesian Computation. - Yura N. Perov; Frank D. Wood (AGI, 2016)

Nonparametric Bayesian models for unsupervised activity recognition and tracking. - Neil Dhir; Yura N. Perov; Frank D. Wood (IROS, 2016)

Bachelor's thesis on generative probabilistic programming (in Russian language, June 2014). - Yura N. Perov (CoRR, 2016)

Applications of Probabilistic Programming (Master's thesis, 2015). - Yura N. Perov (CoRR, 2016)

Spreadsheet Probabilistic Programming. - Mike Wu; Yura N. Perov; Frank D. Wood; Hongseok Yang (CoRR, 2016)

A Universal Marginalizer for Amortized Inference in Generative Models. - Laura Douglas; Iliyan Zarov; Konstantinos Gourgoulias; Chris Lucas 002; Chris Hart; Adam Baker; Maneesh Sahani; Yura Perov; Saurabh Johri (CoRR, 2017)

A comparative study of artificial intelligence and human doctors for the purpose of triage and diagnosis. - Salman Razzaki; Adam Baker; Yura Perov; Katherine Middleton; Janie Baxter; Daniel Mullarkey; Davinder Sangar; Michael Taliercio; Mobasher Butt; Azeem Majeed; Arnold DoRosario; Megan Mahoney; et al. (CoRR, 2018)

Inference Over Programs That Make Predictions. - Yura Perov (CoRR, 2018)

Universal Marginalizer for Amortised Inference and Embedding of Generative Models. - Robert Walecki; Albert Buchard; Kostis Gourgoulias; Chris Hart; Maria Lomeli; Alexandre K. W. Navarro; Max Zwiessele; Yura Perov; Saurabh Johri (CoRR, 2018)

MultiVerse: Causal Reasoning using Importance Sampling in Probabilistic Programming. - Yura Perov; Logan Graham; Kostis Gourgoulias; Jonathan G. Richens; Ciarán M. Lee; Adam Baker; Saurabh Johri (AABI, 2019)

Universal Marginaliser for Deep Amortised Inference for Probabilistic Programs. - Robert Walecki; Kostis Gourgoulias; Adam Baker; Chris Hart; Chris Lucas 002; Max Zwiessele; Albert Buchard; Maria Lomeli; Yura Perov; Saurabh Johri (CoRR, 2019)

Learning medical triage from clinicians using Deep Q-Learning. - Albert Buchard; Baptiste Bouvier; Giulia Prando; Rory Beard; Michail Livieratos; Dan Busbridge; Daniel H. Thompson; Jonathan G. Richens; Yuanzhao Zhang; Adam Baker; Yura Perov; Kostis Gourgoulias; et al. (CoRR, 2020)

Applying Artificial Intelligence Methods for the Estimation of Disease Incidence: The Utility of Language Models. - Yuanzhao Zhang; Robert Walecki; Joanne R. Winter; Felix J. S. Bragman; Sara Lourenco; Christopher Hart; Adam Baker; Yura Perov; Saurabh Johri (Frontiers Digit. Health, 2020)

A Comparison of Artificial Intelligence and Human Doctors for the Purpose of Triage and Diagnosis. - Adam Baker; Yura Perov; Katherine Middleton; Janie Baxter; Daniel Mullarkey; Davinder Sangar; Mobasher Butt; Arnold DoRosario; Saurabh Johri (Frontiers Artif. Intell., 2020)