Driven by data or derived through physics? a review of hybrid physics guided machine learning techniques with cyber-physical system (cps) focus
A multitude of cyber-physical system (CPS) applications, including design, control,
diagnosis, prognostics, and a host of other problems, are predicated on the assumption of …
diagnosis, prognostics, and a host of other problems, are predicated on the assumption of …
Model averaging in ecology: A review of Bayesian, information‐theoretic, and tactical approaches for predictive inference
CF Dormann, JM Calabrese… - Ecological …, 2018 - Wiley Online Library
In ecology, the true causal structure for a given problem is often not known, and several
plausible models and thus model predictions exist. It has been claimed that using weighted …
plausible models and thus model predictions exist. It has been claimed that using weighted …
Mutant clones in normal epithelium outcompete and eliminate emerging tumours
Human epithelial tissues accumulate cancer-driver mutations with age,,,,,,,–, yet tumour
formation remains rare. The positive selection of these mutations suggests that they alter the …
formation remains rare. The positive selection of these mutations suggests that they alter the …
Global patterns of opioid use and dependence: harms to populations, interventions, and future action
We summarise the evidence for medicinal uses of opioids, harms related to the extramedical
use of, and dependence on, these drugs, and a wide range of interventions used to address …
use of, and dependence on, these drugs, and a wide range of interventions used to address …
Benchmarking simulation-based inference
JM Lueckmann, J Boelts, D Greenberg… - International …, 2021 - proceedings.mlr.press
Recent advances in probabilistic modelling have led to a large number of simulation-based
inference algorithms which do not require numerical evaluation of likelihoods. However, a …
inference algorithms which do not require numerical evaluation of likelihoods. However, a …
Sequential neural likelihood: Fast likelihood-free inference with autoregressive flows
G Papamakarios, D Sterratt… - The 22nd international …, 2019 - proceedings.mlr.press
Abstract We present Sequential Neural Likelihood (SNL), a new method for Bayesian
inference in simulator models, where the likelihood is intractable but simulating data from …
inference in simulator models, where the likelihood is intractable but simulating data from …
Weak SINDy for partial differential equations
DA Messenger, DM Bortz - Journal of Computational Physics, 2021 - Elsevier
Abstract Sparse Identification of Nonlinear Dynamics (SINDy) is a method of system
discovery that has been shown to successfully recover governing dynamical systems from …
discovery that has been shown to successfully recover governing dynamical systems from …
Lives saved with vaccination for 10 pathogens across 112 countries in a pre-COVID-19 world
Background: Vaccination is one of the most effective public health interventions. We
investigate the impact of vaccination activities for Haemophilus influenzae type b, hepatitis …
investigate the impact of vaccination activities for Haemophilus influenzae type b, hepatitis …
[HTML][HTML] Metrics to relate COVID-19 wastewater data to clinical testing dynamics
Wastewater surveillance has emerged as a useful tool in the public health response to the
COVID-19 pandemic. While wastewater surveillance has been applied at various scales to …
COVID-19 pandemic. While wastewater surveillance has been applied at various scales to …
The role of vaccination and public awareness in forecasts of Mpox incidence in the United Kingdom
Abstract Beginning in May 2022, Mpox virus spread rapidly in high-income countries
through close human-to-human contact primarily amongst communities of gay, bisexual and …
through close human-to-human contact primarily amongst communities of gay, bisexual and …