Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Ulzega, Simone | - |
| dc.date.accessioned | 2018-07-09T13:32:56Z | - |
| dc.date.available | 2018-07-09T13:32:56Z | - |
| dc.date.issued | 2017-04-11 | - |
| dc.identifier.uri | https://digitalcollection.zhaw.ch/handle/11475/7743 | - |
| dc.description | Invited seminar at ENS, Paris | de_CH |
| dc.description.abstract | Parameter inference is a fundamental problem in data-driven modeling. The aim is to find a so-called posterior distribution of model parameters that are able to explain observed data and can be used for making probabilistic predictions. We propose a novel, exact, very efficient and highly parallelizable Hamiltonian Monte Carlo approach for generating posterior parameter distributions, for stochastic models calibrated to measured time-series. The algorithm is inspired by re-interpreting the posterior distribution as a statistical mechanics partition function of an object akin to a polymer, whose dynamics is confined by both the model and the measurements. | de_CH |
| dc.language.iso | en | de_CH |
| dc.rights | Not specified | de_CH |
| dc.subject.ddc | 003: Systeme | de_CH |
| dc.title | Boosting parameter inference with stochastic models using molecular dynamics and high-performance computing | de_CH |
| dc.type | Vorlesung | de_CH |
| dcterms.type | Text | de_CH |
| zhaw.departement | Life Sciences und Facility Management | de_CH |
| zhaw.organisationalunit | Institut für Computational Life Sciences (ICLS) | de_CH |
| zhaw.originated.zhaw | Yes | de_CH |
| zhaw.webfeed | Biomedical Simulation | de_CH |
| Appears in collections: | Publikationen Life Sciences und Facility Management | |
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Ulzega, S. (2017). Boosting parameter inference with stochastic models using molecular dynamics and high-performance computing.
Ulzega, S. (2017) Boosting parameter inference with stochastic models using molecular dynamics and high-performance computing.
S. Ulzega, Boosting parameter inference with stochastic models using molecular dynamics and high-performance computing. 2017.
ULZEGA, Simone, 2017. Boosting parameter inference with stochastic models using molecular dynamics and high-performance computing
Ulzega, Simone. 2017. Boosting Parameter Inference with Stochastic Models Using Molecular Dynamics and High-Performance Computing.
Ulzega, Simone. Boosting Parameter Inference with Stochastic Models Using Molecular Dynamics and High-Performance Computing. 2017.
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