Dennis Prangle

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 18

Top Topics

Gaussian Process

Sequential Monte Carlo

Variational Inference

Top Venues

Publications

Tennessee Hickling, Dennis Prangle
Flexible Tails for Normalizing Flows. CoRR (2024)
Dennis Prangle, Cecilia Viscardi
Distilling Importance Sampling for Likelihood Free Inference. J. Comput. Graph. Stat. 32 (4) (2023)
Tennessee Hickling, Dennis Prangle
Flexible Tails for Normalising Flows, with Application to the Modelling of Financial Return Data. CoRR (2023)
Vladimiro González-Zelaya, Julián Salas, Dennis Prangle, Paolo Missier
Preprocessing Matters: Automated Pipeline Selection for Fair Classification. MDAI (2023)
Matthew Fisher, Tui Nolan, Matthew Graham, Dennis Prangle, Chris J. Oates
Measure Transport with Kernel Stein Discrepancy. AISTATS (2021)
Vladimiro González-Zelaya, Julián Salas, Dennis Prangle, Paolo Missier
Optimising Fairness Through Parametrised Data Sampling. EDBT (2021)
Thomas Ryder, Dennis Prangle, Andrew Golightly, Isaac Matthews
The neural moving average model for scalable variational inference of state space models. UAI (2021)
Wil O. C. Ward, Tom Ryder, Dennis Prangle, Mauricio A. Álvarez
Black-Box Inference for Non-Linear Latent Force Models. AISTATS (2020)
Rob Geada, Dennis Prangle, Andrew Stephen McGough
Bonsai-Net: One-Shot Neural Architecture Search via Differentiable Pruners. CoRR (2020)
Dennis Prangle
gk: An R Package for the g-and-k and Generalised g-and-h Distributions. R J. 12 (1) (2020)
Wil O. C. Ward, Tom Ryder, Dennis Prangle, Mauricio A. Álvarez
Variational Bridge Constructs for Grey Box Modelling with Gaussian Processes. CoRR (2019)
Tom Ryder, Andrew Golightly, Isaac Matthews, Dennis Prangle
Scalable approximate inference for state space models with normalising flows. CoRR (2019)
Tom Ryder, Andrew Golightly, A. Stephen McGough, Dennis Prangle
Black-Box Autoregressive Density Estimation for State-Space Models. CoRR (2018)
Dennis Prangle, Richard G. Everitt, Theodore Kypraios
A rare event approach to high-dimensional approximate Bayesian computation. Stat. Comput. 28 (4) (2018)
G. S. Rodrigues, Dennis Prangle, Scott A. Sisson
Recalibration: A post-processing method for approximate Bayesian computation. Comput. Stat. Data Anal. 126 (2018)
Thomas Ryder, Andrew Golightly, A. Stephen McGough, Dennis Prangle
Black-Box Variational Inference for Stochastic Differential Equations. ICML (2018)
Richard G. Everitt, Dennis Prangle, Philip Maybank, Mark Bell
Marginal sequential Monte Carlo for doubly intractable models. CoRR (2017)
Dennis Prangle
Lazy ABC. Stat. Comput. 26 (1-2) (2016)
Matthew A. Nunes, Dennis Prangle
abctools: An R Package for Tuning Approximate Bayesian Computation Analyses. R J. 7 (2) (2015)