| Probabilistic inference by program transformation in Hakaru (system description) P Narayanan, J Carette, W Romano, C Shan, R Zinkov Functional and Logic Programming: 13th International Symposium, FLOPS 2016 …, 2016 | 113 | 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 | 112 | 2017 |
| Potential-based Shaping in Model-based Reinforcement Learning. J Asmuth, ML Littman, R Zinkov AAAI, 604-609, 2008 | 106 | 2008 |
| Faithful inversion of generative models for effective amortized inference S Webb, A Golinski, R Zinkov, T Rainforth, YW Teh, F Wood Advances in Neural Information Processing Systems 31, 2018 | 34 | 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 | 31 | 2018 |
| Composing inference algorithms as program transformations R Zinkov, C Shan Proceedings of Uncertainty in Artificial Intelligence, http://auai.org …, 2017 | 29 | 2017 |
| 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 | 17 | 2017 |
| 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 |
| 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 | 4 | 2020 |
| Sensitivity analysis for distributed optimization with resource constraints. E Bowring, Z Yin, R Zinkov, M Tambe AAMAS (1), 633-640, 2009 | 4 | 2009 |
| 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 |
| probKanren: A Simple Probabilistic Extension for microKanren. R Zinkov, WE Byrd ICLP Workshops, 2021 | 1 | 2021 |
| Simulation-Based Inference for Global Health Decisions W CSd, B Gram-Hansen, N Nardelli, A Gambardella, R Zinkov, P Dokania, ... | | 2020 |
| Simulation-Based Inference for Global Health Decisions C Schroeder de Witt, B Gram-Hansen, N Nardelli, A Gambardella, ... arXiv e-prints, arXiv: 2005.07062, 2020 | | 2020 |
| Hasty-A Generative Model Complier F Wood, M Teng, R Zinkov University of Oxford Oxford United Kingdom, 2019 | | 2019 |
| Inference Building Blocks J Carett, O Kiselyov, WI Mohammed, P Narayanan, N Ramsey, ... Indiana University, 2018 | | 2018 |
| Accelerating Program Synthesis in miniKanren R Zinkov, M Ballantyne, GL Rosenblatt, WE Byrd | | |
| 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 | | |
