George Papamakarios

According to our database, George Papamakarios authored at least 22 papers between 2015 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Estimating Gibbs free energies via isobaric-isothermal flows.

Peter Wirnsberger, Borja Ibarz, George Papamakarios

Mach. Learn. Sci. Technol., September, 2023

Equivariant MuZero.

Andreea Deac, Theophane Weber, George Papamakarios

Trans. Mach. Learn. Res., 2023

Gibbs free energies via isobaric-isothermal flows.

Peter Wirnsberger, Borja Ibarz, George Papamakarios

CoRR, 2023

Compositional Score Modeling for Simulation-Based Inference.

Tomas Geffner, George Papamakarios, Andriy Mnih

Proceedings of the International Conference on Machine Learning, 2023

2022

Normalizing flows for atomic solids.

Peter Wirnsberger, George Papamakarios, Borja Ibarz, Sébastien Racanière, Andrew J. Ballard, Alexander Pritzel, Charles Blundell

Mach. Learn. Sci. Technol., 2022

Score Modeling for Simulation-based Inference.

Tomas Geffner, George Papamakarios, Andriy Mnih

CoRR, 2022

A Generalist Neural Algorithmic Learner.

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

Proceedings of the Learning on Graphs Conference, 2022

2021

Normalizing Flows for Probabilistic Modeling and Inference.

George Papamakarios, Eric T. Nalisnick, Danilo Jimenez Rezende, Shakir Mohamed, Balaji Lakshminarayanan

J. Mach. Learn. Res., 2021

The Lipschitz Constant of Self-Attention.

Hyunjik Kim, George Papamakarios, Andriy Mnih

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Causally Correct Partial Models for Reinforcement Learning.

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

CoRR, 2020

Normalizing Flows on Tori and Spheres.

Danilo Jimenez Rezende, George Papamakarios, Sébastien Racanière, Michael S. Albergo, Gurtej Kanwar, Phiala E. Shanahan, Kyle Cranmer

Proceedings of the 37th International Conference on Machine Learning, 2020

On Contrastive Learning for Likelihood-free Inference.

Conor Durkan, Iain Murray, George Papamakarios

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Neural density estimation and likelihood-free inference.

George Papamakarios

PhD thesis, 2019

Neural Density Estimation and Likelihood-free Inference.

George Papamakarios

CoRR, 2019

Cubic-Spline Flows.

Conor Durkan, Artur Bekasov, Iain Murray, George Papamakarios

CoRR, 2019

Neural Spline Flows.

Conor Durkan, Artur Bekasov, Iain Murray, George Papamakarios

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Temporal Difference Variational Auto-Encoder.

Karol Gregor, George Papamakarios, Frederic Besse, Lars Buesing, Theophane Weber

Proceedings of the 7th International Conference on Learning Representations, 2019

Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows.

George Papamakarios, David C. Sterratt, Iain Murray

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Sequential Neural Methods for Likelihood-free Inference.

Conor Durkan, George Papamakarios, Iain Murray

CoRR, 2018

2017

Masked Autoregressive Flow for Density Estimation.

George Papamakarios, Iain Murray, Theo Pavlakou

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation.

George Papamakarios, Iain Murray

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

Distilling Model Knowledge.

George Papamakarios

CoRR, 2015