SCHYMANSKI Stanislaus

University of Luxembourg

Main Referenced Co-authors

HALE, Jack (3)

LEY, Christophe (3)

MINGO NDIWAGO, Damian (3)

Nijzink, Remko (3)

SCHYMANSKI, Emma (1)

Main Referenced Keywords

Replica Exchange Hamiltonian Monte Carlo (2); Thermodynamic integration (2); , Rainfall-runoff models (1); Bayes factor (1); Dynamic models (1);

Main Referenced Disciplines

Mathematics (2)

Physical, chemical, mathematical & earth Sciences: Multidisciplinary, general & others (2)

Civil engineering (1)

Computer science (1)

Engineering, computing & technology: Multidisciplinary, general & others (1)

Publications (total 4)

Search in publications

The most downloaded

100 downloads

MINGO NDIWAGO, D., Nijzink, R., LEY, C., SCHYMANSKI, S., & HALE, J. (24 April 2023). Thermodynamic integration via Replica Exchange Hamiltonian Monte Carlo for faster sampling and model comparison [Paper presentation]. EGU General Assembly, Vienna, Austria. doi:10.5194/egusphere-egu23-2910 https://hdl.handle.net/10993/54462

The most cited

9 citations (OpenAlex)

SCHYMANSKI, E., & SCHYMANSKI, S. (2023). Water science must be Open Science. Nature Water, 1 (1), 4--6. doi:10.1038/s44221-022-00014-z https://hdl.handle.net/10993/54241

https://hdl.handle.net/10993/54462

MINGO NDIWAGO, D., Nijzink, R., LEY, C., SCHYMANSKI, S., & HALE, J. (25 January 2023). Using replica exchange Hamiltonian Monte Carlo and thermodynamic integration for comparison of dynamic rainfall-runoff models [Paper presentation]. Luxembourg-Waseda Conference on Modelling and Inference for Complex Data, Belval, Luxembourg.

https://hdl.handle.net/10993/54843

SCHYMANSKI, E., & SCHYMANSKI, S. (2023). Water science must be Open Science. Nature Water, 1 (1), 4--6. doi:10.1038/s44221-022-00014-z

https://hdl.handle.net/10993/54241

MINGO NDIWAGO, D., Nijzink, R., LEY, C., SCHYMANSKI, S., & HALE, J. (05 June 2022). Using Bayes factors to compare dynamical models of hydrological systems [Paper presentation]. 5th International Conference on Econometrics and Statistics (EcoSta 2022), Kyoto, Japan.

https://hdl.handle.net/10993/51573