Swapnil Mishra | DeepAI

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∙ 05/31/2023

Deep learning and MCMC with aggVAE for shifting administrative boundaries: mapping malaria prevalence in Kenya

Model-based disease mapping remains a fundamental policy-informing tool ...

0 Elizaveta Semenova, et al. ∙

∙ 05/01/2023

A comparison of short-term probabilistic forecasts for the incidence of COVID-19 using mechanistic and statistical time series models

Short-term forecasts of infectious disease spread are a critical compone...

0 Nicolas Banholzer, et al. ∙

∙ 10/31/2022

The interaction of transmission intensity, mortality, and the economy: a retrospective analysis of the COVID-19 pandemic

The COVID-19 pandemic has caused over 6.4 million registered deaths to d...

0 Christian Morgenstern, et al. ∙

∙ 10/25/2022

The uncertainty of infectious disease outbreaks is underestimated

Uncertainty can be classified as either aleatoric (intrinsic randomness)...

0 Matthew J. Penn, et al. ∙

∙ 10/21/2022

Cox-Hawkes: doubly stochastic spatiotemporal Poisson processes

Hawkes processes are point process models that have been used to capture...

0 Xenia Miscouridou, et al. ∙

∙ 10/24/2021

Epidemia: An R Package for Semi-Mechanistic Bayesian Modelling of Infectious Diseases using Point Processes

This article introduces epidemia, an R package for Bayesian, regression-...

0 James A. Scott, et al. ∙

∙ 10/20/2021

Encoding spatiotemporal priors with VAEs for small-area estimation

Gaussian processes (GPs), implemented through multivariate Gaussian dist...

0 Elizaveta Semenova, et al. ∙

∙ 07/12/2021

Unifying the effective reproduction number, incidence, and prevalence under a stochastic age-dependent branching process

Renewal equations are a popular approach used in modelling the number of...

0 Tresnia Berah, et al. ∙

∙ 02/22/2021

Gaussian Process Nowcasting: Application to COVID-19 Mortality Reporting

Updating observations of a signal due to the delays in the measurement p...

16 Iwona Hawryluk, et al. ∙

∙ 12/01/2020

Semi-Mechanistic Bayesian Modeling of COVID-19 with Renewal Processes

We propose a general Bayesian approach to modeling epidemics such as COV...

0 Samir Bhatt, et al. ∙

∙ 09/08/2020

Simulating normalising constants with referenced thermodynamic integration: application to COVID-19 model selection

Model selection is a fundamental part of Bayesian statistical inference;...

19 Iwona Hawryluk, et al. ∙

∙ 07/13/2020

A unified machine learning approach to time series forecasting applied to demand at emergency departments

There were 25.6 million attendances at Emergency Departments (EDs) in En...

198 Michaela A C Vollmer, et al. ∙

∙ 06/30/2020

On the derivation of the renewal equation from an age-dependent branching process: an epidemic modelling perspective

Renewal processes are a popular approach used in modelling infectious di...

0 Swapnil Mishra, et al. ∙

∙ 04/23/2020

Estimating the number of infections and the impact of non-pharmaceutical interventions on COVID-19 in European countries: technical description update

Following the emergence of a novel coronavirus (SARS-CoV-2) and its spre...

0 Seth Flaxman, et al. ∙

∙ 02/17/2020

πVAE: Encoding stochastic process priors with variational autoencoders

Stochastic processes provide a mathematically elegant way model complex ...

8 Swapnil Mishra, et al. ∙

∙ 04/06/2018

Modeling Popularity in Asynchronous Social Media Streams with Recurrent Neural Networks

Understanding and predicting the popularity of online items is an import...

0 Swapnil Mishra, et al. ∙

∙ 08/21/2017

A Tutorial on Hawkes Processes for Events in Social Media

This chapter provides an accessible introduction for point processes, an...

0 Marian-Andrei Rizoiu, et al. ∙

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