SCOPUS 정보 검색 플랫폼

31st International Conference on Machine Learning, ICML 2014

Volumn 4, Issue , 2014, Pages 3351-3359

Gaussian processes for Bayesian estimation in ordinary differential equations

(2) Wang, Yali a Barber, David b

a UNIVERSITÉ LAVAL (Canada)

b UNIVERSITY COLLEGE LONDON (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BAYESIAN NETWORKS; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); LEARNING SYSTEMS; NUMERICAL METHODS; PARAMETER ESTIMATION;

BAYESIAN ESTIMATIONS; BAYESIAN PARAMETER ESTIMATION; COMPUTATIONAL COSTS; DERIVATIVE INFORMATION; GAUSSIAN PROCESS MODELS; GAUSSIAN PROCESSES; GRADIENT MATCHING; NUMERICAL INTEGRATIONS;

ORDINARY DIFFERENTIAL EQUATIONS;

EID: 84919783595 PISSN: None EISSN: None Source Type: Conference Proceeding
DOI: None Document Type: Conference Paper

Times cited : (20)

References (8)

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- Barber, D.¹

2
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- Accelerating Bayesian inference over nonlinear differential equations with Gaussian processes
- Calderhead, B., Girolami, M., and Lawrence, N. D. Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes. In NIPS, 2008.
- (2008) NIPS
- Calderhead, B.¹ Girolami, M.² Lawrence, N.D.³

3
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- Ode parameter inference using adaptive gradient matching with Gaussian processes
- Dondelinger, F., Filippone, M., Rogers, S., and Husmeier, D. ODE parameter inference using adaptive gradient matching with Gaussian processes. In AISTATS, 2013.
- (2013) AISTATS
- Dondelinger, F.¹ Filippone, M.² Rogers, S.³ Husmeier, D.⁴

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- Graepel, T.¹

5
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- MIT Press
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- (2009) Probabilistic Graphical Models: Principles and Technique
- Koller, D.¹ Friedman, N.²

6
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- Parameter estimation for differential equations: A generalized smoothing approach
- Ramsay, J., Hooker, G., Campbell, D., and Cao, J. Parameter Estimation for Differential Equations: A Generalized Smoothing Approach. Journal of the Royal Statistical Society: Series B, 69(5):741-796, 2007.
- (2007) Journal of the Royal Statistical Society: Series B , vol.69 , Issue.5 , pp. 741-796
- Ramsay, J.¹ Hooker, G.² Campbell, D.³ Cao, J.⁴

7
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- Derivative observations in Gaussian process models of dynamic systems
- Solak, E., Murray-Smith, R., Leithead, W. E., Leith, D. J., and Rasmussen, C. E. Derivative observations in Gaussian Process models of dynamic systems. In NIPS, 2002.
- (2002) NIPS
- Solak, E.¹ Murray-Smith, R.² Leithead, W.E.³ Leith, D.J.⁴ Rasmussen, C.E.⁵

8
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- Bayesian ranking of biochemical system models
- Vyshemirsky, V. and Girolami, M. Bayesian ranking of biochemical system models. Bioinformatics, 24:833- 839, 2008.
- (2008) Bioinformatics , vol.24 , pp. 833-839
- Vyshemirsky, V.¹ Girolami, M.²

* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.