Distilling Model Knowledge. - George Papamakarios (CoRR, 2015)

Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation. - George Papamakarios; Iain Murray 001 (NIPS, 2016)

Masked Autoregressive Flow for Density Estimation. - George Papamakarios; Iain Murray 001; Theo Pavlakou (NIPS, 2017)

Sequential Neural Methods for Likelihood-free Inference. - Conor Durkan; George Papamakarios; Iain Murray 001 (CoRR, 2018)

Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows. - George Papamakarios; David C. Sterratt; Iain Murray 001 (AISTATS, 2019)

Temporal Difference Variational Auto-Encoder. - Karol Gregor; George Papamakarios; Frederic Besse; Lars Buesing; Theophane Weber (ICLR, 2019)

Neural Spline Flows. - Conor Durkan; Artur Bekasov; Iain Murray 001; George Papamakarios (NeurIPS, 2019)

Cubic-Spline Flows. - Conor Durkan; Artur Bekasov; Iain Murray 001; George Papamakarios (CoRR, 2019)

Neural Density Estimation and Likelihood-free Inference. - George Papamakarios (CoRR, 2019)

Neural density estimation and likelihood-free inference. - George Papamakarios (2019)

On Contrastive Learning for Likelihood-free Inference. - Conor Durkan; Iain Murray 001; George Papamakarios (ICML, 2020)

Normalizing Flows on Tori and Spheres. - Danilo Jimenez Rezende; George Papamakarios; Sébastien Racanière; Michael S. Albergo; Gurtej Kanwar; Phiala E. Shanahan; Kyle Cranmer (ICML, 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 001; Jovana Mitrovic; Frederic Besse; et al. (CoRR, 2020)

The Lipschitz Constant of Self-Attention. - Hyunjik Kim; George Papamakarios; Andriy Mnih (ICML, 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)

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; et al. (LoG, 2022)

Score Modeling for Simulation-based Inference. - Tomas Geffner; George Papamakarios; Andriy Mnih (CoRR, 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)

Compositional Score Modeling for Simulation-Based Inference. - Tomas Geffner; George Papamakarios; Andriy Mnih (ICML, 2023)

Gibbs free energies via isobaric-isothermal flows. - Peter Wirnsberger; Borja Ibarz; George Papamakarios (CoRR, 2023)

Equivariant MuZero. - Andreea Deac; Theophane Weber; George Papamakarios (Trans. Mach. Learn. Res., 2023)

Estimating Gibbs free energies via isobaric-isothermal flows. - Peter Wirnsberger; Borja Ibarz; George Papamakarios (Mach. Learn. Sci. Technol., 2023)