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Andreas Munk
Andreas Munk
PhD in Computer Science, University of British Columbia
Bestätigte E-Mail-Adresse bei ammunk.com - Startseite
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Zitiert von
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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
662019
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
502019
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
132018
Attention for inference compilation
W Harvey, A Munk, AG Baydin, A Bergholm, F Wood
arXiv preprint arXiv:1910.11961, 2019
112019
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
52022
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
52019
Uncertain evidence in probabilistic models and stochastic simulators
A Munk, A Mead, F Wood
International Conference on Machine Learning, 25486-25500, 2023
42023
Bayesian transfer learning for deep networks
J Wohlert, A Munk, S Sengupta, F Laumann
ViXra, 2018
22018
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, ...
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