Dennis Prangle

22 papers A* 2A 3B 2Journal 14Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
Minimum Distance Summaries for Robust Neural Posterior Estimation.
CoRR
Sherman Khoo, Dennis Prangle, Song Liu, Mark Beaumont
2025 A* conf
Flexible Tails for Normalizing Flows.
ICML
Tennessee Hickling, Dennis Prangle
2024 J jnl
Flexible Tails for Normalizing Flows.
CoRR
Tennessee Hickling, Dennis Prangle
2023 J jnl
Distilling Importance Sampling for Likelihood Free Inference.
J. Comput. Graph. Stat.
Dennis Prangle, Cecilia Viscardi
2023 — conf
Flexible Tails for Normalising Flows, with Application to the Modelling of Financial Return Data.
PKDD/ECML Workshops (5)
Tennessee Hickling, Dennis Prangle
2023 J jnl
Flexible Tails for Normalising Flows, with Application to the Modelling of Financial Return Data.
CoRR
Tennessee Hickling, Dennis Prangle
2023 B conf
Preprocessing Matters: Automated Pipeline Selection for Fair Classification.
MDAI
Vladimiro González-Zelaya, Julián Salas, Dennis Prangle, Paolo Missier
2021 A conf
Measure Transport with Kernel Stein Discrepancy.
AISTATS
Matthew Fisher, Tui Nolan, Matthew M. Graham, Dennis Prangle, Chris J. Oates
2021 B conf
Optimising Fairness Through Parametrised Data Sampling.
EDBT
Vladimiro González-Zelaya, Julián Salas, Dennis Prangle, Paolo Missier
2021 A conf
The neural moving average model for scalable variational inference of state space models.
UAI
Thomas Ryder, Dennis Prangle, Andrew Golightly, Isaac Matthews
2020 A conf
Black-Box Inference for Non-Linear Latent Force Models.
AISTATS
Wil O. C. Ward, Tom Ryder, Dennis Prangle, Mauricio A. Álvarez
2020 J jnl
Bonsai-Net: One-Shot Neural Architecture Search via Differentiable Pruners.
CoRR
Rob Geada, Dennis Prangle, Andrew Stephen McGough
2020 J jnl
gk: An R Package for the g-and-k and Generalised g-and-h Distributions.
R J.
Dennis Prangle
2019 J jnl
Scalable approximate inference for state space models with normalising flows.
CoRR
Tom Ryder, Andrew Golightly, Isaac Matthews, Dennis Prangle
2019 J jnl
Variational Bridge Constructs for Grey Box Modelling with Gaussian Processes.
CoRR
Wil O. C. Ward, Tom Ryder, Dennis Prangle, Mauricio A. Álvarez
2018 J jnl
A rare event approach to high-dimensional approximate Bayesian computation.
Stat. Comput.
Dennis Prangle, Richard G. Everitt, Theodore Kypraios
2018 J jnl
Black-Box Autoregressive Density Estimation for State-Space Models.
CoRR
Tom Ryder, Andrew Golightly, A. Stephen McGough, Dennis Prangle
2018 A* conf
Black-Box Variational Inference for Stochastic Differential Equations.
ICML
Thomas Ryder, Andrew Golightly, A. Stephen McGough, Dennis Prangle
2018 J jnl
Recalibration: A post-processing method for approximate Bayesian computation.
Comput. Stat. Data Anal.
G. S. Rodrigues, Dennis Prangle, Scott A. Sisson
2017 J jnl
Marginal sequential Monte Carlo for doubly intractable models.
CoRR
Richard G. Everitt, Dennis Prangle, Philip Maybank, Mark Bell
2016 J jnl
Lazy ABC.
Stat. Comput.
Dennis Prangle
2015 J jnl
abctools: An R Package for Tuning Approximate Bayesian Computation Analyses.
R J.
Matthew A. Nunes, Dennis Prangle