| Etalumis: Bringing probabilistic programming to scientific simulators at scale AG Baydin, L Shao, W Bhimji, L Heinrich, L Meadows, J Liu, A Munk, ... Proceedings of the international conference for high performance computing …, 2019 | 66 | 2019 |
| Efficient probabilistic inference in the quest for physics beyond the standard model AG Baydin, L Shao, W Bhimji, L Heinrich, S Naderiparizi, A Munk, J Liu, ... Advances in neural information processing systems 32, 2019 | 50 | 2019 |
| 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 | 23* | 2022 |
| Semi-supervised sleep-stage scoring based on single channel EEG AM Munk, KV Olesen, SW Gangstad, LK Hansen 2018 IEEE international conference on acoustics, speech and signal …, 2018 | 13 | 2018 |
| Attention for inference compilation W Harvey, A Munk, AG Baydin, A Bergholm, F Wood arXiv preprint arXiv:1910.11961, 2019 | 11 | 2019 |
| 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 |
| 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 |
| Uncertain evidence in probabilistic models and stochastic simulators A Munk, A Mead, F Wood International Conference on Machine Learning, 25486-25500, 2023 | 4 | 2023 |
| Bayesian transfer learning for deep networks J Wohlert, A Munk, S Sengupta, F Laumann ViXra, 2018 | 2 | 2018 |
| Prabhat and F. Wood (2019). Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale AG Baydin, L Shao, W Bhimji, L Heinrich, LF Meadows, J Liu, A Munk, ... Proceedings of the International Conference for High Performance Computing …, 0 | 2 | |
| Accelerating Bayesian inference in probabilistic programming A Munk University of British Columbia, 2023 | | 2023 |
| Assisting the Adversary to Improve GAN Training A Munk, W Harvey, F Wood 2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | | 2021 |
| Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale BA Günes, L Shao, W Bhimji, L Heinrich, L Meadows, J Liu, A Munk, ... Proceedings of SC19, 2019 | | 2019 |
| Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model A Güneş Baydin, L Heinrich, W Bhimji, L Shao, S Naderiparizi, A Munk, ... arXiv e-prints, arXiv: 1807.07706, 2018 | | 2018 |
| Acoustic levitation of particles AM Munk | | 2016 |
| Effective Approximate Inference for Nested Simulators BJ Gram-Hansen, A Golinski, CS de Witt, S Naderiparizi, A Scibior, ... | | |
Frank WoodUniversity of British ColumbiaVerified email at cs.ubc.ca
