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09/14/2023
System Effects in Identifying Risk-Optimal Data Requirements for Digital Twins of Structures
Structural Health Monitoring (SHM) technologies offer much promise to th...
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07/14/2023
Training Discrete Energy-Based Models with Energy Discrepancy
Training energy-based models (EBMs) on discrete spaces is challenging be...
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07/12/2023
Energy Discrepancies: A Score-Independent Loss for Energy-Based Models
Energy-based models are a simple yet powerful class of probabilistic mod...
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04/28/2023
Using Perturbation to Improve Goodness-of-Fit Tests based on Kernelized Stein Discrepancy
Kernelized Stein discrepancy (KSD) is a score-based discrepancy widely u...
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02/11/2023
A High-dimensional Convergence Theorem for U-statistics with Applications to Kernel-based Testing
We prove a convergence theorem for U-statistics of degree two, where the...
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09/10/2022
Batch Bayesian Optimization via Particle Gradient Flows
Bayesian Optimisation (BO) methods seek to find global optima of objecti...
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07/13/2022
Spatial anomaly detection with optimal transport
This manuscript outlines an automated anomaly detection framework for je...
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06/09/2022
A Spectral Representation of Kernel Stein Discrepancy with Application to Goodness-of-Fit Tests for Measures on Infinite Dimensional Hilbert Spaces
Kernel Stein discrepancy (KSD) is a widely used kernel-based measure of ...
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03/07/2022
Prior-informed Uncertainty Modelling with Bayesian Polynomial Approximations
Orthogonal polynomial approximations form the foundation to a set of wel...
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11/15/2021
Theoretical Guarantees for the Statistical Finite Element Method
The statistical finite element method (StatFEM) is an emerging probabili...
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04/07/2021
Ensemble Inference Methods for Models With Noisy and Expensive Likelihoods
The increasing availability of data presents an opportunity to calibrate...
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12/31/2020
Blade Envelopes Part II: Multiple Objectives and Inverse Design
Blade envelopes offer a set of data-driven tolerance guidelines for manu...
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11/22/2020
Blade Envelopes Part I: Concept and Methodology
Blades manufactured through flank and point milling will likely exhibit ...
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10/07/2020
Data Driven Density Functional Theory: A case for Physics Informed Learning
We propose a novel data-driven approach to solving a classical statistic...
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09/03/2020
Probabilistic Gradients for Fast Calibration of Differential Equation Models
Calibration of large-scale differential equation models to observational...
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08/25/2020
A Kernel Two-Sample Test for Functional Data
We propose a nonparametric two-sample test procedure based on Maximum Me...
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06/12/2020
Scalable Control Variates for Monte Carlo Methods via Stochastic Optimization
Control variates are a well-established tool to reduce the variance of M...
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06/19/2019
Minimum Stein Discrepancy Estimators
When maximum likelihood estimation is infeasible, one often turns to sco...
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06/13/2019
Statistical Inference for Generative Models with Maximum Mean Discrepancy
While likelihood-based inference and its variants provide a statisticall...
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11/21/2016