98 citations · 101 across the 9 of their papers we have counts for
9 papers
Deep Variational Inference Symbolic Regression
James Butterworth, Gevik Grigorian, Alejandro DiazDelaO
Symbolic regression discovers explicit, interpretable equations without assuming a functional form in advance. A Bayesian approach strengthens this through probability distribution…
Niching Importance Sampling for Multi-modal Rare-event Simulation
Hugh J. Kinnear, F. A. DiazDelaO
This paper proposes niching importance sampling, a framework that combines concepts from reliability analysis, e.g. Markov chains, importance sampling, and relative cross entropy m…
Integrative Analysis and Imputation of Multiple Data Streams via Deep Gaussian Processes
Ali Akbar Septiandri, Deyu Ming, F. Alejandro DiazDelaO +2
Healthcare data, particularly in critical care settings, presents three key challenges for analysis. First, physiological measurements come from different sources but are inherentl…
Niching Subset Simulation
Hugh J. Kinnear, F. A. DiazDelaO
Subset Simulation is a Markov chain Monte Carlo method used to compute small failure probabilities in structural reliability problems. This is done by iteratively sampling from nes…
Adaptive multilevel subset simulation with selective refinement
Daniel Elfverson, Robert Scheichl, Simon Weissmann +1
In this work we propose an adaptive multilevel version of subset simulation to estimate the probability of rare events for complex physical systems. Given a sequence of nested fail…
History matching with probabilistic emulators and active learning
Alfredo Garbuno-Inigo, F. Alejandro DiazDelaO, Konstantin M. Zuev
The scientific understanding of real-world processes has dramatically improved over the years through computer simulations. Such simulators represent complex mathematical models th…
Contributed Discussion of "A Bayesian Conjugate Gradient Method"
Francois-Xavier Briol, Francisco A. Diaz De la O, Peter O. Hristov
We would like to congratulate the authors of "A Bayesian Conjugate Gradient Method" on their insightful paper, and welcome this publication which we firmly believe will become a fu…
Bayesian updating and model class selection with Subset Simulation
F. A. DiazDelaO, A. Garbuno-Inigo, S. K. Au +1
Identifying the parameters of a model and rating competitive models based on measured data has been among the most important but challenging topics in modern science and engineerin…
Transitional annealed adaptive slice sampling for Gaussian process hyper-parameter estimation
A. Garbuno-Inigo, F. A. DiazDelaO, K. M. Zuev
Surrogate models have become ubiquitous in science and engineering for their capability of emulating expensive computer codes, necessary to model and investigate complex phenomena.…