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Learning Models, Supermodels, and Ensemble Models of Dynamic Systems
Published on 2014-04-242063 Views
Presentation
Learning Models, Supermodels, and Ensemble Models of Dynamic Systems00:00
Learning Models of Dynamic Systems03:35:36
Learning Models of Dynamic Systems: An Example10:30:44
Learning Models of Dynamic Systems: A Real-world Example from Ecology20:33:27
A Machine Learning Approach to Learning Models of Dynamic Systems - 131:28:13
A Machine Learning Approach to Learning Models of Dynamic Systems - 244:57:54
Using Domain Knowledge78:47:07
Data and Knowledge-Driven Modeling105:44:43
Process Models (PM)134:04:50
PM: Qualitative Aspect162:13:56
PM: Quantitative Aspect174:14:47
Inductive Process Modelling183:32:24
Libraries of Domain Knowledge214:13:48
Hierarchies of Species and Processes235:20:46
Alternative Formulations243:03:37
Modeling Task Specification256:15:39
IPM: Searching for Process Models280:41:50
IPM: Generate Models - 1293:30:47
IPM: Generate Models - 2314:11:55
ProBMoT: A SW Platform for IPM320:30:34
Parameter Estimation in ProBMoT338:30:07
Applications of IPM351:24:55
Modeling Aquatic Ecosystems373:51:16
Automated Modeling of Lake EcoSystems379:33:05
Applications in Systems Biology/ ‘Reconstructing’ Biological Networks385:59:12
‘Reconstructing’ Biological Networks416:33:03
Modeling Knowledge for Metabolic Networks428:25:07
Example Application: Glycolisys447:13:46
Induced Glycolysis Network451:24:34
Systems vs. Synthetic Biology457:37:47
ProBMoT for Synthetic Biology471:55:24
Case Study: Biochemical Adaptation - 1495:27:16
Case Study: Biochemical Adaptation - 2507:16:05
Design of Biological Circuits with Complex Behaviours530:49:25
Case Study: Repressilator542:51:25
Case Study: Coupled Repressilators544:19:42
Summary I545:54:01
Model Ensembles and Supermodels553:21:58
Learning Lorenz Models and Supermodels580:45:42
Lorenz: A Library for Process-based Modeling597:53:14
Lorenz: An Example Process-based Model609:06:57
A Process-based Library for Supermodeling618:57:27
An Example Supermodel: Components638:21:13
An Example Supermodel: Couplings650:18:36
Learning a Component Model from Data662:25:28
Learning Couplings in a Supermodel672:32:49
Ensemble Models in Machine Learning678:53:25
Using Ensemble of Models701:41:59
Constructing an Ensemble of Models706:12:06
Constructing of Different Training Sets: Bagging707:54:52
(Bootstrap) Sampling from Time Series719:02:23
Learning Ensemble Models with ProBMoT734:44:56
Summary II747:07:22
Thank you!752:39:13
DS-2014: 17th International Conference on Discovery Science760:33:21