Potential-based Shaping in Model-based Reinforcement Learning. J Asmuth, ML Littman, R Zinkov AAAI, 604-609, 2008 | 81 | 2008 |

Probabilistic inference by program transformation in Hakaru (system description) P Narayanan, J Carette, W Romano, C Shan, R Zinkov International Symposium on Functional and Logic Programming, 62-79, 2016 | 61 | 2016 |

Using synthetic data to train neural networks is model-based reasoning TA Le, AG Baydin, R Zinkov, F Wood 2017 International Joint Conference on Neural Networks (IJCNN), 3514-3521, 2017 | 53 | 2017 |

Composing inference algorithms as program transformations R Zinkov, C Shan Proceedings of Uncertainty in Artificial Intelligence, http://auai.org …, 2017 | 21 | 2017 |

Faithful inversion of generative models for effective amortized inference S Webb, A Golinski, R Zinkov, N Siddharth, T Rainforth, YW Teh, F Wood Advances in Neural Information Processing Systems, 3070-3080, 2018 | 17 | 2018 |

Querying word embeddings for similarity and relatedness FT Asr, R Zinkov, M Jones Proceedings of the 2018 Conference of the North American Chapter of the …, 2018 | 16 | 2018 |

End-to-end training of differentiable pipelines across machine learning frameworks M Milutinovic, AG Baydin, R Zinkov, W Harvey, D Song, F Wood, W Shen | 8 | 2017 |

Sensitivity analysis for distributed optimization with resource constraints E Bowring, Z Yin, R Zinkov, M Tambe Proceedings of The 8th International Conference on Autonomous Agents and …, 2009 | 4 | 2009 |

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 | 1 | 2019 |

Efficient Bayesian inference for nested simulators B Gram-Hansen, CS de Witt, R Zinkov, S Naderiparizi, A Scibior, A Munk, ... | 1 | 2019 |

Simulation-Based Inference for Global Health Decisions CS de Witt, B Gram-Hansen, N Nardelli, A Gambardella, R Zinkov, ... arXiv preprint arXiv:2005.07062, 2020 | | 2020 |

Simulation-Based Inference for Global Health Decisions C Schroeder de Witt, B Gram-Hansen, N Nardelli, A Gambardella, ... arXiv, arXiv: 2005.07062, 2020 | | 2020 |

Hasty-A Generative Model Complier F Wood, M Teng, R Zinkov University of Oxford Oxford United Kingdom, 2019 | | 2019 |

Automating Expectation Maximixation R Zinkov | | |

Building blocks for exact and approximate inference J Carette, P Narayanan, W Romano, C Shan, R Zinkov | | |

Efficient Probabilistic Programming Languages R Zinkov | | |

Probabilistic Programming in R with Bruno R Zinkov, CC Shan | | |