Cover Image

Surrogate Modelling of Proton Dose with Monte Carlo Dropout Uncertainty Quantification

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Pim, Aaron, Pryer, Tristan
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Data Analysis, Statistics and Probability Applications
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Multi-level Monte Carlo Dropout for Efficient Uncertainty Quantification
by: Pim, Aaron, et al.
Published: (2026)

History Matching under Uncertainty of Geological Scenarios with Implicit Geological Realism Control with Generative Deep Learning and Graph Convolutions
by: Shishaev, Gleb, et al.
Published: (2025)

Toward Model-Agnostic Detection of New Physics Using Data-Driven Signal Regions
by: Yi, Soheun, et al.
Published: (2024)

From Occurrence to Consequence: A Comprehensive Data-driven Analysis of Building Fire Risk
by: Ma, Chenzhi, et al.
Published: (2025)

Integrating Bayesian Spectral Deconvolution and Expert Scientific Reasoning for Robust Peak Estimation
by: Okubo, Hayato, et al.
Published: (2026)

Reservoir Static Property Estimation Using Nearest-Neighbor Neural Network
by: Wang, Yuhe
Published: (2024)

GeoConformal prediction: a model-agnostic framework of measuring the uncertainty of spatial prediction
by: Lou, Xiayin, et al.
Published: (2024)

Markov Chain Monte Carlo with Gaussian Process Emulation for a 1D Hemodynamics Model of CTEPH
by: Kachabi, Amirreza, et al.
Published: (2024)

Physics-informed Information Field Theory for Modeling Physical Systems with Uncertainty Quantification
by: Alberts, Alex, et al.
Published: (2023)

Inherited or produced? Inferring protein production kinetics when protein counts are shaped by a cell's division history
by: Pessoa, Pedro, et al.
Published: (2025)

Learning Complex Physical Regimes via Coverage-oriented Uncertainty Quantification: An application to the Critical Heat Flux
by: Cazzola, Michele, et al.
Published: (2026)

EnScale: Temporally-consistent multivariate generative downscaling via proper scoring rules
by: Schillinger, Maybritt, et al.
Published: (2025)

Smart Ensemble Learning Framework for Predicting Groundwater Heavy Metal Pollution
by: Ansah-Narh, T., et al.
Published: (2026)

Inferring Mobility Reductions from COVID-19 Disease Spread along the Urban-Rural Gradient
by: Paltra, Sydney, et al.
Published: (2025)

Change point detection in ERA5 ground temperature time series
by: A., Fatemeh Aghaei, et al.
Published: (2025)

Titanic overconfidence -- dark uncertainty can sink hybrid metrology for semiconductor manufacturing
by: Dixson, Ronald G., et al.
Published: (2026)

PHYSTAT Informal Review: Marginalizing versus Profiling of Nuisance Parameters
by: Cousins, Robert D., et al.
Published: (2024)

Correlation analysis of the dispersion of SARS-CoV-2 in Mexico
by: López, Pablo Carlos, et al.
Published: (2026)

Blume-Capel model: Estimation of a three stable state network for $-\bf 1$, $\bf 0$ and $\bf +1$ data
by: Waldorp, Lourens, et al.
Published: (2026)

A Tutorial on Bayesian Analysis of Linear Shock Compression Data
by: Bernstein, Jason, et al.
Published: (2026)

Uncertainty Quantification with Bayesian Higher Order ReLU KANs
by: Giroux, James, et al.
Published: (2024)

A Priori Uncertainty Quantification of Reacting Turbulence Closure Models using Bayesian Neural Networks
by: Pash, Graham, et al.
Published: (2024)

Calibration in Machine Learning Uncertainty Quantification: beyond consistency to target adaptivity
by: Pernot, Pascal
Published: (2023)

Particle Filtering for Non-Deterministic Electrocardiographic Imaging
by: Lagracie, Emma, et al.
Published: (2025)

Physics-Informed Neural Network-based Reliability Analysis of Buried Pipelines
by: Taraghi, Pouya, et al.
Published: (2025)

Bayesian Multistate Bennett Acceptance Ratio Methods
by: Ding, Xinqiang
Published: (2023)

Multidimensional Deconvolution with Profiling
by: Zhu, Huanbiao, et al.
Published: (2024)

Learning Likelihood Ratios with Neural Network Classifiers
by: Rizvi, Shahzar, et al.
Published: (2023)

Lithological Controls on the Permeability of Geologic Faults: Surrogate Modeling and Sensitivity Analysis
by: Lu, Hannah, et al.
Published: (2025)

High-Precision Surrogate Modeling for Uncertainty Quantification in Complex Slurry Flows
by: Elkarii, Marwane, et al.
Published: (2024)

Least Squares as Random Walks
by: Kostinski, Alexander, et al.
Published: (2025)

Information-theoretic Quantification of High-order Feature Effects in Classification Problems
by: Lazic, Ivan, et al.
Published: (2025)

Causal Hierarchy in the Financial Market Network -- Uncovered by the Helmholtz-Hodge-Kodaira Decomposition
by: Wand, Tobias, et al.
Published: (2024)

Coarse graining correlation matrices according to macrostructures: Financial markets as a paradigm
by: Martínez-Ramos, M. Mijaíl, et al.
Published: (2024)

Probabilistic Spatiotemporal Modeling of Day-Ahead Wind Power Generation with Input-Warped Gaussian Processes
by: Li, Qiqi, et al.
Published: (2024)

Investigating the effect of non-resonant background variation on the CARS data analysis and classification
by: Junjuri, Rajendhar, et al.
Published: (2024)

Structural and Lagrangian properties of analogue ensembles to characterize multifractality of stochastic processes
by: Granero-Belinchon, Carlos
Published: (2026)

Uncertainty estimation via ensembles of deep learning models and dropout layers for seismic traces
by: Messuti, Giovanni, et al.
Published: (2024)

The Information Content of Quasar Variability Light Curves: How Well Can we Infer Stochastic Model Parameters?
by: Brewer, Brendon J., et al.
Published: (2026)

Inferring Grain Size Distributions from Magnetic Hysteresis in M-type Hexaferrites
by: Ataei, Masoud, et al.
Published: (2025)