Andreas Munk
Andreas Munk
PhD in Computer Science, University of British Columbia
Verified email at - Homepage
Cited by
Cited by
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
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
Deep probabilistic surrogate networks for universal simulator approximation
A Munk, A Scibior, AG Baydin, A Stewart, G Fernlund, A Poursartip, ...
arXiv preprint arXiv:1910.11950 25, 2019
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
Attention for inference compilation
W Harvey, A Munk, AG Baydin, A Bergholm, F Wood
arXiv preprint arXiv:1910.11961, 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
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
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
Bayesian Transfer Learning for Deep Networks
J Wohlert, AM Munk, S Sengupta, F Laumann
Uncertain evidence in probabilistic models and stochastic simulators
A Munk, A Mead, F Wood
International Conference on Machine Learning, 25486-25500, 2023
Accelerating Bayesian inference in probabilistic programming
A Munk
University of British Columbia, 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
Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale
BA GŁnes, L Shao, W Bhimji, L Heinrich, L Meadows, J Liu, A Munk, ...
Proceedings of SC19, 2019
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model
A GŁneş Baydin, L Heinrich, W Bhimji, L Shao, S Naderiparizi, A Munk, ...
arXiv e-prints, arXiv: 1807.07706, 2018
Acoustic levitation of particles
AM Munk
Effective Approximate Inference for Nested Simulators
BJ Gram-Hansen, A Golinski, CS de Witt, S Naderiparizi, A Scibior, ...
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