84 citations · 88 across the 4 of their papers we have counts for
11 papers
A Case Study in Model Failure? COVID-19 Daily Deaths and ICU Bed Utilisation Predictions in New York State
Vincent Chin, Noelle I. Samia, Roman Marchant +4
Forecasting models have been influential in shaping decision-making in the COVID-19 pandemic. However, there is concern that their predictions may have been misleading. Here, we di…
Learning as We Go: An Examination of the Statistical Accuracy of COVID19 Daily Death Count Predictions
Roman Marchant, Noelle I. Samia, Ori Rosen +2
This paper provides a formal evaluation of the predictive performance of a model (and its various updates) developed by the Institute for Health Metrics and Evaluation (IHME) for p…
AdaptSPEC-X: Covariate Dependent Spectral Modeling of Multiple Nonstationary Time Series
Michael Bertolacci, Ori Rosen, Edward Cripps +1
We present a method for the joint analysis of a panel of possibly nonstationary time series. The approach is Bayesian and uses a covariate-dependent infinite mixture model to incor…
Structured Variational Inference in Continuous Cox Process Models
Virginia Aglietti, Edwin V. Bonilla, Theodoros Damoulas +1
We propose a scalable framework for inference in an inhomogeneous Poisson process modeled by a continuous sigmoidal Cox process that assumes the corresponding intensity function is…
Bayesian Nonparametric Adaptive Spectral Density Estimation for Financial Time Series
Nick James, Roman Marchant, Richard Gerlach +1
Discrimination between non-stationarity and long-range dependency is a difficult and long-standing issue in modelling financial time series. This paper uses an adaptive spectral te…
Efficiency and robustness in Monte Carlo sampling of 3-D geophysical inversions with Obsidian v0.1.2: Setting up for success
Richard Scalzo, David Kohn, Hugo Olierook +4
The rigorous quantification of uncertainty in geophysical inversions is a challenging problem. Inversions are often ill-posed and the likelihood surface may be multi-modal; propert…