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ORCIDGeorge Papamakarios
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2020 – today
- 2023
[j4]Peter Wirnsberger
, Borja Ibarz, George Papamakarios:
Estimating Gibbs free energies via isobaric-isothermal flows. Mach. Learn. Sci. Technol. 4(3): 35039 (2023)- [j3]Andreea Deac, Theophane Weber, George Papamakarios:
Equivariant MuZero. Trans. Mach. Learn. Res. 2023 (2023) - [c10]Tomas Geffner, George Papamakarios, Andriy Mnih:
Compositional Score Modeling for Simulation-Based Inference. ICML 2023: 11098-11116 - [i17]Andreea Deac, Théophane Weber, George Papamakarios:
Equivariant MuZero. CoRR abs/2302.04798 (2023) - [i16]Peter Wirnsberger, Borja Ibarz, George Papamakarios:
Gibbs free energies via isobaric-isothermal flows. CoRR abs/2305.13233 (2023) - 2022
- [j2]Peter Wirnsberger, George Papamakarios, Borja Ibarz, Sébastien Racanière, Andrew J. Ballard, Alexander Pritzel, Charles Blundell:
Normalizing flows for atomic solids. Mach. Learn. Sci. Technol. 3(2): 25009 (2022) - [c9]Borja Ibarz, Vitaly Kurin, George Papamakarios, Kyriacos Nikiforou, Mehdi Bennani, Róbert Csordás, Andrew Joseph Dudzik, Matko Bosnjak, Alex Vitvitskyi, Yulia Rubanova, Andreea Deac, Beatrice Bevilacqua, Yaroslav Ganin, Charles Blundell, Petar Velickovic:
A Generalist Neural Algorithmic Learner. LoG 2022: 2 - [i15]Borja Ibarz, Vitaly Kurin, George Papamakarios, Kyriacos Nikiforou, Mehdi Bennani, Róbert Csordás, Andrew Dudzik, Matko Bosnjak, Alex Vitvitskyi, Yulia Rubanova, Andreea Deac, Beatrice Bevilacqua, Yaroslav Ganin, Charles Blundell, Petar Velickovic:
A Generalist Neural Algorithmic Learner. CoRR abs/2209.11142 (2022) - [i14]Tomas Geffner, George Papamakarios, Andriy Mnih:
Score Modeling for Simulation-based Inference. CoRR abs/2209.14249 (2022) - 2021
- [j1]George Papamakarios, Eric T. Nalisnick, Danilo Jimenez Rezende, Shakir Mohamed, Balaji Lakshminarayanan:
Normalizing Flows for Probabilistic Modeling and Inference. J. Mach. Learn. Res. 22: 57:1-57:64 (2021) - [c8]Hyunjik Kim, George Papamakarios, Andriy Mnih:
The Lipschitz Constant of Self-Attention. ICML 2021: 5562-5571 - 2020
- [c7]Conor Durkan, Iain Murray, George Papamakarios:
On Contrastive Learning for Likelihood-free Inference. ICML 2020: 2771-2781 - [c6]Danilo Jimenez Rezende, George Papamakarios, Sébastien Racanière, Michael S. Albergo, Gurtej Kanwar, Phiala E. Shanahan, Kyle Cranmer:
Normalizing Flows on Tori and Spheres. ICML 2020: 8083-8092 - [i13]Danilo Jimenez Rezende, George Papamakarios, Sébastien Racanière, Michael S. Albergo, Gurtej Kanwar, Phiala E. Shanahan, Kyle Cranmer:
Normalizing Flows on Tori and Spheres. CoRR abs/2002.02428 (2020) - [i12]Danilo J. Rezende, Ivo Danihelka, George Papamakarios, Nan Rosemary Ke, Ray Jiang, Theophane Weber, Karol Gregor, Hamza Merzic, Fabio Viola, Jane Wang, Jovana Mitrovic, Frederic Besse, Ioannis Antonoglou, Lars Buesing:
Causally Correct Partial Models for Reinforcement Learning. CoRR abs/2002.02836 (2020) - [i11]Conor Durkan, Iain Murray, George Papamakarios:
On Contrastive Learning for Likelihood-free Inference. CoRR abs/2002.03712 (2020) - [i10]Hyunjik Kim, George Papamakarios, Andriy Mnih:
The Lipschitz Constant of Self-Attention. CoRR abs/2006.04710 (2020)
2010 – 2019
- 2019
- [b1]George Papamakarios:
Neural density estimation and likelihood-free inference. University of Edinburgh, UK, 2019 - [c5]George Papamakarios, David C. Sterratt, Iain Murray:
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows. AISTATS 2019: 837-848 - [c4]Karol Gregor, George Papamakarios, Frederic Besse, Lars Buesing, Theophane Weber:
Temporal Difference Variational Auto-Encoder. ICLR 2019 - [c3]Conor Durkan, Artur Bekasov, Iain Murray, George Papamakarios:
Neural Spline Flows. NeurIPS 2019: 7509-7520 - [i9]Conor Durkan, Artur Bekasov, Iain Murray, George Papamakarios:
Cubic-Spline Flows. CoRR abs/1906.02145 (2019) - [i8]Conor Durkan, Artur Bekasov, Iain Murray, George Papamakarios:
Neural Spline Flows. CoRR abs/1906.04032 (2019) - [i7]George Papamakarios:
Neural Density Estimation and Likelihood-free Inference. CoRR abs/1910.13233 (2019) - [i6]George Papamakarios, Eric T. Nalisnick, Danilo Jimenez Rezende, Shakir Mohamed, Balaji Lakshminarayanan:
Normalizing Flows for Probabilistic Modeling and Inference. CoRR abs/1912.02762 (2019) - 2018
- [i5]George Papamakarios, David C. Sterratt, Iain Murray:
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows. CoRR abs/1805.07226 (2018) - [i4]Conor Durkan, George Papamakarios, Iain Murray:
Sequential Neural Methods for Likelihood-free Inference. CoRR abs/1811.08723 (2018) - 2017
- [c2]George Papamakarios, Iain Murray, Theo Pavlakou:
Masked Autoregressive Flow for Density Estimation. NIPS 2017: 2338-2347 - [i3]George Papamakarios, Theo Pavlakou, Iain Murray:
Masked Autoregressive Flow for Density Estimation. CoRR abs/1705.07057 (2017) - 2016
- [c1]George Papamakarios, Iain Murray:
Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation. NIPS 2016: 1028-1036 - [i2]George Papamakarios, Iain Murray:
Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation. CoRR abs/1605.06376 (2016) - 2015
- [i1]George Papamakarios:
Distilling Model Knowledge. CoRR abs/1510.02437 (2015)
Coauthor Index
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