LAUSR

Exploring gravitational-wave detection and parameter inference using deep learning methods

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1 Published in 2021 at "Classical and Quantum Gravity"

DOI: 10.1088/1361-6382/ac0455

Abstract: We explore machine learning methods to detect gravitational waves (GW) from binary black hole (BBH) mergers using deep learning (DL) algorithms. The DL networks are trained with gravitational waveforms obtained from BBH mergers with component… read more here.

Keywords: parameter inference; using deep; learning methods; deep learning ... See more keywords

PyDREAM: high-dimensional parameter inference for biological models in python

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0 Published in 2018 at "Bioinformatics"

DOI: 10.1093/bioinformatics/btx626

Abstract: Abstract Summary Biological models contain many parameters whose values are difficult to measure directly via experimentation and therefore require calibration against experimental data. Markov chain Monte Carlo (MCMC) methods are suitable to estimate multivariate posterior… read more here.

Keywords: high dimensional; parameter inference; biological models; pydream ... See more keywords

Model Selection and Parameter Inference in Phylogenetics Using Nested Sampling

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0 Published in 2019 at "Systematic Biology"

DOI: 10.1093/sysbio/syy050

Abstract: &NA; Bayesian inference methods rely on numerical algorithms for both model selection and parameter inference. In general, these algorithms require a high computational effort to yield reliable estimates. One of the major challenges in phylogenetics… read more here.

Keywords: parameter inference; model selection; selection parameter; nested sampling ... See more keywords

Modelling and parameter inference of predator–prey dynamics in heterogeneous environments using the direct integral approach

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0 Published in 2017 at "Journal of The Royal Society Interface"

DOI: 10.1098/rsif.2016.0525

Abstract: Most bacterial habitats are topographically complex in the micro scale. Important examples include the gastrointestinal and tracheal tracts, and the soil. Although there are myriad theoretical studies that explore the role of spatial structures on… read more here.

Keywords: inference predator; parameter inference; dynamics heterogeneous; heterogeneous environments ... See more keywords

The impact of experimental design choices on parameter inference for models of growing cell colonies

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1 Published in 2018 at "Royal Society Open Science"

DOI: 10.1098/rsos.180384

Abstract: To better understand development, repair and disease progression, it is useful to quantify the behaviour of proliferative and motile cell populations as they grow and expand to fill their local environment. Inferring parameters associated with… read more here.

Keywords: growth; cell; parameter inference; experimental design ... See more keywords

Heterodyned likelihood for rapid gravitational wave parameter inference

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0 Published in 2021 at "Physical Review D"

DOI: 10.1103/physrevd.104.104054

Abstract: Inferring the source properties of a gravitational wave signal has traditionally been very computationally intensive and time consuming. In recent years, several techniques have been developed that can significantly reduce the computational cost while delivering… read more here.

Keywords: likelihood rapid; gravitational wave; parameter inference; heterodyned likelihood ... See more keywords

Parameter inference for stochastic single-cell dynamics from lineage tree data

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0 Published in 2017 at "BMC Systems Biology"

DOI: 10.1186/s12918-017-0425-1

Abstract: BackgroundWith the advance of experimental techniques such as time-lapse fluorescence microscopy, the availability of single-cell trajectory data has vastly increased, and so has the demand for computational methods suitable for parameter inference with this type… read more here.

Keywords: single cell; parameter inference; cell; lineage tree ... See more keywords

Parameter inference for stochastic biochemical models from perturbation experiments parallelised at the single cell level

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1 Published in 2022 at "PLoS Computational Biology"

DOI: 10.1371/journal.pcbi.1009950

Abstract: Understanding and characterising biochemical processes inside single cells requires experimental platforms that allow one to perturb and observe the dynamics of such processes as well as computational methods to build and parameterise models from the… read more here.

Keywords: parameter inference; experimental platforms; parameter; single cell ... See more keywords