George Papamakarios

Orcid: 0000-0002-2551-6543

According to our database1, George Papamakarios authored at least 22 papers between 2015 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2023
Estimating Gibbs free energies via isobaric-isothermal flows.
Mach. Learn. Sci. Technol., September, 2023

Equivariant MuZero.
Trans. Mach. Learn. Res., 2023

Gibbs free energies via isobaric-isothermal flows.
CoRR, 2023

Compositional Score Modeling for Simulation-Based Inference.
Proceedings of the International Conference on Machine Learning, 2023

2022
Normalizing flows for atomic solids.
Mach. Learn. Sci. Technol., 2022

Score Modeling for Simulation-based Inference.
CoRR, 2022


2021
Normalizing Flows for Probabilistic Modeling and Inference.
J. Mach. Learn. Res., 2021

The Lipschitz Constant of Self-Attention.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Causally Correct Partial Models for Reinforcement Learning.
CoRR, 2020

Normalizing Flows on Tori and Spheres.
Proceedings of the 37th International Conference on Machine Learning, 2020

On Contrastive Learning for Likelihood-free Inference.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Neural density estimation and likelihood-free inference.
PhD thesis, 2019

Neural Density Estimation and Likelihood-free Inference.
CoRR, 2019

Cubic-Spline Flows.
CoRR, 2019

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

Temporal Difference Variational Auto-Encoder.
Proceedings of the 7th International Conference on Learning Representations, 2019

Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Sequential Neural Methods for Likelihood-free Inference.
CoRR, 2018

2017
Masked Autoregressive Flow for Density Estimation.
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.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015
Distilling Model Knowledge.
CoRR, 2015


  Loading...