Search results
- 1.0585931 - ÚOCHB 2025 RIV AT eng C - Conference Paper (international conference)
Kirjner, A. - Yim, J. - Samusevich, Raman - Bracha, S. - Jaakkola, T. - Barzilay, R. - Fiete, I.
Improving protein optimization with smoothed fitness landscapes.
ICLR 2024. The Twelfth International Conference on Learning Representations. Vienna: ICLR, 2024.
[ICLR 2024. International Conference on Learning Representations /12./. Vienna (AT), 07.05.2024-11.05.2024]
Research Infrastructure: e-INFRA CZ II - 90254
Institutional support: RVO:61388963
Keywords : protein design * discrete optimization * protein engineering * markov chain monte carlo * graph signal processing
OECD category: Other biological topics
https://openreview.net/forum?id=rxlF2Zv8x0
Permanent Link: https://hdl.handle.net/11104/0353566File Download Size Commentary Version Access 0585931.pdf 0 1.5 MB Publisher’s postprint open-access - 2.0571878 - ÚGN 2024 RIV CZ eng C - Conference Paper (international conference)
Bérešová, Simona
Numerical realization of the Bayesian inversion accelerated using surrogate models.
Programs and Algorithms of Numerical Mathematics 21 : Proceedings of Seminar. Praha: Institute of Mathematics CAS Prague, 2023 - (Chleboun, J.; Kůs, P.; Papež, J.; Rozložník, M.; Segeth, K.; Šístek, J.), s. 25-36. ISBN 978-80-85823-73-8.
[Programs and Algorithms of Numerical Mathematics /21./. Jablonec nad Nisou (CZ), 19.06.2022-24.06.2022]
R&D Projects: GA TA ČR(CZ) TK02010118
Institutional support: RVO:68145535
Keywords : Bayesian inversion * delayed-acceptance Metropolis-Hastings * Markov chain Monte Carlo * surrogate model
OECD category: Applied mathematics
https://dml.cz/bitstream/handle/10338.dmlcz/703185/PANM_21-2022-1_6.pdf
Permanent Link: https://hdl.handle.net/11104/0342777File Download Size Commentary Version Access UGN_0571878.pdf 2 804.1 KB Other require - 3.0565076 - ÚGN 2023 CZ eng D - Thesis
Bérešová, Simona
Bayesian approach to the identification of parameters of differential equations.
Ústav geoniky AV ČR, v. v. i. Defended: Fakulta elektrotechniky a informatiky, VŠB-TUO. 09.06.2022. - Ostrava: VŠB - Technická univerzita Ostrava, 2022. 122 s.
Institutional support: RVO:68145535
Keywords : Bayesian inversion * deflated conjugate gradients * delayed-acceptance Metropolis-Hastings * Markov chain Monte Carlo * material parameter identification * surrogate model
OECD category: Statistics and probability
Permanent Link: https://hdl.handle.net/11104/0336621File Download Size Commentary Version Access UGN_0565076.pdf 2 7.8 MB Other open-access - 4.0556601 - ÚGN 2023 RIV CZ cze L4 - Software
Bérešová, Simona
SurrDAMH 1.0.
[SurrDAMH 1.0.]
Internal code: SurrDAMH 1.0 ; 2022
Technical parameters: Knihovna surrDAMH verze 1.0 slouží pro numerickou realizaci Bayesovské inverze pomocí metod Markov chain Monte Carlo.
Economic parameters: Knihovna surrDAMH verze 1.0
R&D Projects: GA TA ČR(CZ) TK02010118
EU Projects: European Commission(XE) 847593 - EURAD
Institutional support: RVO:68145535
Keywords : Bayesian inversion * Markov chain Monte Carlo * surrogate model
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
https://github.com/dom0015/surrDAMH/releases/tag/v1.0
Permanent Link: http://hdl.handle.net/11104/0330778 - 5.0505335 - ÚTIA 2020 RIV CZ eng D - Thesis
Papež, Milan
Monte Carlo-Based Identification Strategies for State-Space Models.
Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií. Defended: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií. 16.5.2019. - Brno: Vysoké učení technické v Brně, 2019. 224 s.
R&D Projects: GA ČR(CZ) GA18-15970S
Institutional support: RVO:67985556
Keywords : sequential Monte Carlo * particle Markov chain Monte Carlo * nonlinear and non-Gaussian state-space models * transfer learning
OECD category: Statistics and probability
http://library.utia.cas.cz/separaty/2019/AS/papez-0505335.pdf
Permanent Link: http://hdl.handle.net/11104/0296952 - 6.0410887 - UTIA-B 20020101 DK eng V - Research Report
Moller, J. - Beneš, Viktor - Bodlák, M. - Waagepetersen, R.
Bayesian Analysis of Log Gaussian Cox Processes for Disease Mapping.
Aarhus: MSP MaPhySto, 2002. 24 s. Research Report, 3.
R&D Projects: GA AV ČR IAA1075201
Institutional research plan: CEZ:AV0Z1075907
Keywords : population intensity * Langevin-Hastings algorithm * Markov chain Monte Carlo
Subject RIV: BB - Applied Statistics, Operational Research
Permanent Link: http://hdl.handle.net/11104/0130974 - 7.0410852 - UTIA-B 20020066 DK eng V - Research Report
Beneš, Viktor - Bodlák, M. - Moller, J.
Bayesian Analysis of Log Gaussian Cox Processes for Disease Mapping.
Aalborg: Aalborg University, 2002. 24 s. Research Report, R-02-2001.
R&D Projects: GA AV ČR IAA1075201
Institutional research plan: CEZ:AV0Z1075907
Keywords : population intensity * Langevin-Hastings algorithm * Markov chain Monte Carlo
Subject RIV: BB - Applied Statistics, Operational Research
Permanent Link: http://hdl.handle.net/11104/0130939 - 8.0346287 - ÚTIA 2011 RIV NL eng J - Journal Article
Swart, Jan M. - Vrbenský, Karel
Numerical analysis of the rebellious voter model.
Journal of Statistical Physics. Roč. 140, č. 5 (2010), s. 873-899. ISSN 0022-4715. E-ISSN 1572-9613
R&D Projects: GA ČR GA201/09/1931; GA MŠMT 1M0572
Institutional research plan: CEZ:AV0Z10750506
Keywords : rebellious voter model * parity conservation * exactly solvable model * coexistence * interface tightness * cancellative systems * Markov chain Monte Carlo
Subject RIV: BA - General Mathematics
Impact factor: 1.447, year: 2010
http://library.utia.cas.cz/separaty/2010/SI/swart-numerical analysis of the rebellious voter model.pdf
Permanent Link: http://hdl.handle.net/11104/0187355 - 9.0040977 - ÚTIA 2007 RIV US eng J - Journal Article
Janžura, Martin - Nielsen, Jan
A simulated annealing-based method for learning Bayesian networks from statistical data.
[Metoda učení bayesovských sítí, založená na simulovaném žíhání.]
International Journal of Intelligent Systems. Roč. 21, č. 3 (2006), s. 335-348. ISSN 0884-8173. E-ISSN 1098-111X
R&D Projects: GA ČR GA201/03/0478
Institutional research plan: CEZ:AV0Z10750506
Keywords : Bayesian network * simulated annealing * Markov Chain Monte Carlo
Subject RIV: BA - General Mathematics
Impact factor: 0.429, year: 2006
Permanent Link: http://hdl.handle.net/11104/0134579