Dennis Prangle

According to our database, Dennis Prangle authored at least 19 papers between 2015 and 2024.

Collaborative distances:

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

2024

Flexible Tails for Normalizing Flows.

Tennessee Hickling, Dennis Prangle

CoRR, 2024

2023

Distilling Importance Sampling for Likelihood Free Inference.

Dennis Prangle, Cecilia Viscardi

J. Comput. Graph. Stat., 2023

Flexible Tails for Normalising Flows, with Application to the Modelling of Financial Return Data.

Tennessee Hickling, Dennis Prangle

CoRR, 2023

Preprocessing Matters: Automated Pipeline Selection for Fair Classification.

Vladimiro González-Zelaya, Julián Salas, Dennis Prangle, Paolo Missier

Proceedings of the Modeling Decisions for Artificial Intelligence, 2023

2021

The neural moving average model for scalable variational inference of state space models.

Thomas Ryder, Dennis Prangle, Andrew Golightly, Isaac Matthews

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Optimising Fairness Through Parametrised Data Sampling.

Vladimiro González-Zelaya, Julián Salas, Dennis Prangle, Paolo Missier

Proceedings of the 24th International Conference on Extending Database Technology, 2021

Measure Transport with Kernel Stein Discrepancy.

Matthew Fisher, Tui Nolan, Matthew M. Graham, Dennis Prangle, Chris J. Oates

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

gk: An R Package for the g-and-k and Generalised g-and-h Distributions.

Dennis Prangle

R J., 2020

Bonsai-Net: One-Shot Neural Architecture Search via Differentiable Pruners.

Rob Geada, Dennis Prangle, Andrew Stephen McGough

CoRR, 2020

Black-Box Inference for Non-Linear Latent Force Models.

Wil O. C. Ward, Tom Ryder, Dennis Prangle, Mauricio A. Álvarez

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Scalable approximate inference for state space models with normalising flows.

Tom Ryder, Andrew Golightly, Isaac Matthews, Dennis Prangle

CoRR, 2019

Variational Bridge Constructs for Grey Box Modelling with Gaussian Processes.

Wil O. C. Ward, Tom Ryder, Dennis Prangle, Mauricio A. Álvarez

CoRR, 2019

2018

A rare event approach to high-dimensional approximate Bayesian computation.

Dennis Prangle, Richard G. Everitt, Theodore Kypraios

Stat. Comput., 2018

Recalibration: A post-processing method for approximate Bayesian computation.

G. S. Rodrigues, Dennis Prangle, Scott A. Sisson

Comput. Stat. Data Anal., 2018

Black-Box Autoregressive Density Estimation for State-Space Models.

Tom Ryder, Andrew Golightly, A. Stephen McGough, Dennis Prangle

CoRR, 2018

Black-Box Variational Inference for Stochastic Differential Equations.

Thomas Ryder, Andrew Golightly, A. Stephen McGough, Dennis Prangle

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Marginal sequential Monte Carlo for doubly intractable models.

Richard G. Everitt, Dennis Prangle, Philip Maybank, Mark Bell

CoRR, 2017

2016

Lazy ABC.

Dennis Prangle

Stat. Comput., 2016

2015

abctools: An R Package for Tuning Approximate Bayesian Computation Analyses.

Matthew A. Nunes, Dennis Prangle

R J., 2015