George Papamakarios

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Iain MurraySchool of Informatics, University of EdinburghAdresse e-mail validée de ed.ac.uk
Danilo Jimenez RezendeEllison Institute of TechnologyAdresse e-mail validée de eit.org
Theo PavlakouPhD student, The University of EdinburghAdresse e-mail validée de ed.ac.uk
Artur BekasovAmazonAdresse e-mail validée de amazon.com
Balaji LakshminarayananSenior Staff Research Scientist at Google DeepMindAdresse e-mail validée de google.com
Eric NalisnickAssistant Professor, Johns Hopkins UniversityAdresse e-mail validée de jhu.edu
Sébastien RacanièreResearch Scientist, DeepMindAdresse e-mail validée de google.com
Shakir MohamedResearch Director, Google DeepMindAdresse e-mail validée de deepmind.com
Theophane WeberResearch Scientist at DeepMindAdresse e-mail validée de google.com
Peter WirnsbergerIsomorphic LabsAdresse e-mail validée de google.com
Charles BlundellResearch Scientist at DeepMindAdresse e-mail validée de google.com
Lars BuesingGoogle DeepMindAdresse e-mail validée de google.com
Andriy MnihResearch Scientist at Google DeepMindAdresse e-mail validée de cs.toronto.edu
Alexander PritzelDeepmindAdresse e-mail validée de google.com
Andy BallardGoogle DeepMindAdresse e-mail validée de google.com
Frederic BesseDeepMindAdresse e-mail validée de google.com
David C SterrattUniversity of EdinburghAdresse e-mail validée de ed.ac.uk
Kyle CranmerUniversity of Wisconsin-MadisonAdresse e-mail validée de wisc.edu
Gurtej KanwarUniversity of EdinburghAdresse e-mail validée de ed.ac.uk
Phiala ShanahanMassachusetts Institute of TechnologyAdresse e-mail validée de mit.edu

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George Papamakarios

Google DeepMind

Adresse e-mail validée de google.com - Page d'accueil

Machine Learning


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Gemini: a family of highly capable multimodal models G Team, R Anil, S Borgeaud, JB Alayrac, J Yu, R Soricut, J Schalkwyk, ... arXiv preprint arXiv:2312.11805, 2023	2513	2023
Normalizing Flows for Probabilistic Modeling and Inference G Papamakarios, E Nalisnick, DJ Rezende, S Mohamed, ... Journal of Machine Learning Research 22 (57), 1-64, 2021	1980	2021
Masked autoregressive flow for density estimation G Papamakarios, T Pavlakou, I Murray Advances in neural information processing systems 30, 2017	1648	2017
Neural spline flows C Durkan, A Bekasov, I Murray, G Papamakarios Advances in Neural Information Processing Systems, 7511-7522, 2019	888	2019
Fast ε-free inference of simulation models with Bayesian conditional density estimation G Papamakarios, I Murray Advances in Neural Information Processing Systems, 1028-1036, 2016	474	2016
Sequential neural likelihood: Fast likelihood-free inference with autoregressive flows G Papamakarios, D Sterratt, I Murray The 22nd International Conference on Artificial Intelligence and Statistics …, 2019	410	2019
The DeepMind JAX Ecosystem I Babuschkin, K Baumli, A Bell, S Bhupatiraju, J Bruce, P Buchlovsky, ... URL http://github. com/deepmind, 2020	206*	2020
Normalizing flows on tori and spheres DJ Rezende, G Papamakarios, S Racaniere, M Albergo, G Kanwar, ... International Conference on Machine Learning, 8083-8092, 2020	175	2020
The lipschitz constant of self-attention H Kim, G Papamakarios, A Mnih International Conference on Machine Learning, 5562-5571, 2021	167	2021
Temporal difference variational auto-encoder K Gregor, G Papamakarios, F Besse, L Buesing, T Weber arXiv preprint arXiv:1806.03107, 2018	156	2018
On contrastive learning for likelihood-free inference C Durkan, I Murray, G Papamakarios International Conference on Machine Learning, 2771-2781, 2020	139	2020
nflows: normalizing flows in PyTorch C Durkan, A Bekasov, I Murray, G Papamakarios Version v0 14 (10.5281), 2020	108*	2020
Targeted free energy estimation via learned mappings P Wirnsberger, AJ Ballard, G Papamakarios, S Abercrombie, S Racanière, ... The Journal of Chemical Physics 153 (14), 2020	89	2020
Cubic-Spline Flows C Durkan, A Bekasov, I Murray, G Papamakarios arXiv preprint arXiv:1906.02145, 2019	89	2019
A generalist neural algorithmic learner B Ibarz, V Kurin, G Papamakarios, K Nikiforou, M Bennani, R Csordás, ... Learning on Graphs Conference, 2: 1-2: 23, 2022	71	2022
Neural density estimation and likelihood-free inference G Papamakarios arXiv preprint arXiv:1910.13233, 2019	66	2019
Normalizing flows for atomic solids P Wirnsberger, G Papamakarios, B Ibarz, S Racaniere, AJ Ballard, ... Machine Learning: Science and Technology 3 (2), 025009, 2022	47	2022
Causally Correct Partial Models for Reinforcement Learning DJ Rezende, I Danihelka, G Papamakarios, NR Ke, R Jiang, T Weber, ... arXiv preprint arXiv:2002.02836, 2020	37	2020
Compositional Score Modeling for Simulation-Based Inference T Geffner, G Papamakarios, A Mnih	31*	2023
Sequential Neural Methods for Likelihood-free Inference C Durkan, G Papamakarios, I Murray arXiv preprint arXiv:1811.08723, 2018	30	2018

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