Pandemic lock-down, isolation, and exit policies based on machine learning predictions
Theodoros Evgeniou, Mathilde Fekom, Anton Ovchinnikov, Raphael Porcher, Camille Pouchol, Nicolas Vayatis
| Year of publication: |
[2022] ; Revised version of 2020/22/DSC
|
|---|---|
| Authors: | Evgeniou, Theodoros ; Fekom, Mathilde ; Ovchinnikov, Anton ; Porcher, Raphael ; Pouchol, Camille ; Vayatis, Nicolas |
| Publisher: |
[Fontainebleau] : INSEAD |
| Subject: | Epidemic Models | SIR | Machine Learning | Personalized Risk Management | COVID-19 | Coronavirus | Künstliche Intelligenz | Artificial intelligence | Epidemie | Epidemic | Risikomanagement | Risk management | Prognoseverfahren | Forecasting model |
| Extent: | 1 Online-Ressource (circa 14 Seiten) Illustrationen |
|---|---|
| Series: | Faculty & research / Insead : working paper series. - Fontainebleau : [Verlag nicht ermittelbar], ZDB-ID 2112291-X. - Vol. 2022, 09 |
| Type of publication: | Book / Working Paper |
| Type of publication (narrower categories): | Graue Literatur ; Non-commercial literature ; Arbeitspapier ; Working Paper |
| Language: | English |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10013175888