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2019:groups:tools:start [2019/06/22 18:00] roberto.ruiz_de_austri |
2019:groups:tools:start [2019/06/26 16:09] andy.buckley |
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// Please add your name to the projects you are interested in contributing to: // | // Please add your name to the projects you are interested in contributing to: // | ||
- | * [[2019:groups:tools:likelihoods|Likelihood construction and applications]] | + | * [[2019:groups:tools:likelihoods|Likelihood construction and applications (see also SR corrs/ortho)]] |
* [[2019:groups:tools:recastcmp|Recasting/fastsim tool & method comparisons]] | * [[2019:groups:tools:recastcmp|Recasting/fastsim tool & method comparisons]] | ||
- | * [[2019:groups:tools:searchmeas|Search/measurement compatibility]] | + | * [[2019:groups:tools:searchmeas|Search/measurement compatibility and complementarity]] |
* [[2019:groups:tools:interop|Reinterpretation tool interoperability]] | * [[2019:groups:tools:interop|Reinterpretation tool interoperability]] | ||
* [[2019:groups:tools:llp|Long-lived particle recasting]] | * [[2019:groups:tools:llp|Long-lived particle recasting]] | ||
* [[2019:groups:tools:adl|Analysis description languages]] | * [[2019:groups:tools:adl|Analysis description languages]] | ||
- | * [[2019:groups:tools:correlations | Correlations between signal regions of analyses ]] | + | * [[2019:groups:tools:correlations | Correlations/orthogonality between analyses' signal regions ]] |
- | | + | * ML projects are located in the [[2019:participants:start|participants-only section]] |
- | == Contur == | ||
- | If you are interested in a session on learning to install and run Contur please sign up [[2019:groups:tools:contur|here]] and we will schedule something early in the week. | ||
== Reinterpretation Forum statement == | == Reinterpretation Forum statement == | ||
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* CMS open data portal: http://opendata.cern.ch/docs/about-cms | * CMS open data portal: http://opendata.cern.ch/docs/about-cms | ||
- | == Machine Learning: Regression and classification == | + | == Machine Learning: all projects == |
- | === Library of regression and classification networks | + | see protected pages |
- | Keras/Tensorflow and Scikit-learn to start | + | |
- | Library of Training data, maybe connected to hep-data (database) | + | |
- | + | ||
- | Train regression on the following: | + | |
- | - electroweak cross-section in pMSSM19 (DeepXs, ...) | + | |
- | - cross sections Wprime, Zprime (how many dimensions?) | + | |
- | - Doublet Higgs model (6 dim) | + | |
- | + | ||
- | Train likelihoods: | + | |
- | - global fits Gambit Xenoda data (train on likehoods on different observables, e.g. only colliderbit) | + | |
- | - Higgs model with many nuisance parameters (100?) | + | |
- | + | ||
- | Train on observables: | + | |
- | - example relic density | + | |
- | + | ||
- | Train on reconstruction efficiencies: | + | |
- | - LLSps | + | |
- | + | ||
- | (want to share code for the networks...) | + | |
- | + | ||
- | + | ||
- | Output: | + | |
- | - git repositories for networks | + | |
- | - Xenodo data | + | |
- | - talk with hepdata | + | |
- | - paper | + | |
- | - prototype code for the network library | + | |
- | + | ||
- | + | ||
- | Other info: | + | |
- | - How to sample ? Depends on goal, proposed active learning etc. | + | |