메뉴 건너뛰기




Volumn , Issue , 2013, Pages

Approximate Gaussian process inference for the drift of stochastic differential equations

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; DIFFERENTIAL EQUATIONS; GAUSSIAN DISTRIBUTION;

EID: 84898952981     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (66)

References (16)
  • 1
    • 84860609370 scopus 로고    scopus 로고
    • Variational learning of inducing variables in sparse Gaussian processes
    • Michalis K. Titsias. Variational learning of inducing variables in sparse Gaussian processes. JMLR WC&P, 5:567-574, 2009.
    • (2009) JMLR WC&P , vol.5 , pp. 567-574
    • Titsias, M.K.1
  • 2
    • 84877766069 scopus 로고    scopus 로고
    • Expectation propagation in gaussian process dynamical systems
    • P. Bartlett, F.C.N. Pereira, C.J.C. Burges, L. Bottou, and K.Q.Weinberger, editors
    • Marc Deisenroth and ShakirMohamed. Expectation propagation in Gaussian process dynamical systems. In P. Bartlett, F.C.N. Pereira, C.J.C. Burges, L. Bottou, and K.Q.Weinberger, editors, Advances in Neural Information Processing Systems 25, pages 2618-2626. 2012.
    • (2012) Advances in Neural Information Processing Systems , vol.25 , pp. 2618-2626
    • Deisenroth, M.1    Mohamed, S.2
  • 3
    • 67650998865 scopus 로고    scopus 로고
    • GP-BayesFilters: Bayesian filtering using Gaussian process prediction and observation models
    • July
    • Jonathan Ko and Dieter Fox. GP-BayesFilters: Bayesian filtering using Gaussian process prediction and observation models. Autonomous Robots, 27(1):75-90, July 2009.
    • (2009) Autonomous Robots , vol.27 , Issue.1 , pp. 75-90
    • Ko, J.1    Fox, D.2
  • 4
    • 85161993754 scopus 로고    scopus 로고
    • Variational inference for diffusion processes
    • J. C. Platt, D. Koller, Y. Singer, and S. Roweis, editors MIT Press, Cambridge, MA
    • Cédric Archambeau, Manfred Opper, Yuan Shen, Dan Cornford, and John Shawe-Taylor. Variational inference for diffusion processes. In J.C. Platt, D. Koller, Y. Singer, and S. Roweis, editors, Advances in Neural Information Processing Systems 20, pages 17-24. MIT Press, Cambridge, MA, 2008.
    • (2008) Advances in Neural Information Processing Systems , vol.20 , pp. 17-24
    • Archambeau, C.1    Opper, M.2    Shen, Y.3    Cornford, D.4    Shawe-Taylor, J.5
  • 5
    • 85162004913 scopus 로고    scopus 로고
    • Learning networks of stochastic differential equations
    • J. Lafferty, C. K. I. Williams, J. Shawe-Taylor, R.S. Zemel, and A. Culotta, editors
    • José Bento Ayres Pereira, Morteza Ibrahimi, and Andrea Montanari. Learning networks of stochastic differential equations. In J. Lafferty, C. K. I. Williams, J. Shawe-Taylor, R.S. Zemel, and A. Culotta, editors, Advances in Neural Information Processing Systems 23, pages 172-180. 2010.
    • (2010) Advances in Neural Information Processing Systems , vol.23 , pp. 172-180
    • Pereira, J.B.A.1    Ibrahimi, M.2    Montanari, A.3
  • 6
    • 85162503676 scopus 로고    scopus 로고
    • Variational learning for recurrent spiking networks
    • J. Shawe-Taylor, R.S. Zemel, P. Bartlett, F.C.N. Pereira, and K.Q. Weinberger, editors
    • Danilo J. Rezende, Daan Wierstra, and Wulfram Gerstner. Variational learning for recurrent spiking networks. In J. Shawe-Taylor, R.S. Zemel, P. Bartlett, F.C.N. Pereira, and K.Q. Weinberger, editors, Advances in Neural Information Processing Systems 24, pages 136-144. 2011.
    • (2011) Advances in Neural Information Processing Systems , vol.24 , pp. 136-144
    • Rezende, D.J.1    Wierstra, D.2    Gerstner, W.3
  • 7
    • 84896466821 scopus 로고    scopus 로고
    • The coloured noise expansion and parameter estimation of diffusion processes
    • P. Bartlett, F.C.N. Pereira, C.J.C. Burges, L. Bottou, and K.Q. Weinberger, editors
    • Simon Lyons, Amos Storkey, and Simo Sarkka. The coloured noise expansion and parameter estimation of diffusion processes. In P. Bartlett, F.C.N. Pereira, C.J.C. Burges, L. Bottou, and K.Q. Weinberger, editors, Advances in Neural Information Processing Systems 25, pages 1961-1969. 2012.
    • (2012) Advances in Neural Information Processing Systems , vol.25 , pp. 1961-1969
    • Lyons, S.1    Storkey, A.2    Sarkka, S.3
  • 8
    • 84865519492 scopus 로고    scopus 로고
    • Nonparametric estimation of diffusions: A differential equations approach
    • Omiros Papaspiliopoulos, Yvo Pokern, Gareth O. Roberts, and Andrew M. Stuart. Nonparametric estimation of diffusions: a differential equations approach. Biometrika, 99(3):511-531, 2012.
    • (2012) Biometrika , vol.99 , Issue.3 , pp. 511-531
    • Papaspiliopoulos, O.1    Pokern, Y.2    Roberts, G.O.3    Stuart, A.M.4
  • 9
    • 84869108779 scopus 로고    scopus 로고
    • Posterior consistency via precision operators for Bayesian nonparametric drift estimation in SDEs
    • Yvo Pokern, Andrew M. Stuart, and J.H. van Zanten. Posterior consistency via precision operators for Bayesian nonparametric drift estimation in SDEs. Stochastic Processes and their Applications, 123(2):603-628, 2013.
    • (2013) Stochastic Processes and Their Applications , vol.123 , Issue.2 , pp. 603-628
    • Pokern, Y.1    Stuart, A.M.2    Van Zanten, J.H.3
  • 12
    • 4644256184 scopus 로고    scopus 로고
    • TAP Gibbs free energy, belief propagation and sparsity
    • In T. G. Dietterich, S. Becker, and Z. Ghahramani, editors MIT Press
    • Lehel Csat ó, Manfred Opper, and Ole Winther. TAP Gibbs free energy, belief propagation and sparsity. In T. G. Dietterich, S. Becker, and Z. Ghahramani, editors, Advances in Neural Information Processing Systems 14, pages 657-663. MIT Press, 2002.
    • (2002) Advances in Neural Information Processing Systems , vol.14 , pp. 657-663
    • Csat, Ó.L.1    Opper, M.2    Winther, O.3
  • 14
    • 85162005633 scopus 로고    scopus 로고
    • Approximate inference in continuous time Gaussian-jump processes
    • J. Lafferty, C. K. I. Williams, J. Shawe-Taylor, R.S. Zemel, and A. Culotta, editors
    • Manfred Opper, Andreas Ruttor, and Guido Sanguinetti. Approximate inference in continuous time Gaussian-jump processes. In J. Lafferty, C. K. I. Williams, J. Shawe-Taylor, R.S. Zemel, and A. Culotta, editors, Advances in Neural Information Processing Systems 23, pages 1831-1839. 2010.
    • (2010) Advances in Neural Information Processing Systems , vol.23 , pp. 1831-1839
    • Opper, M.1    Ruttor, A.2    Sanguinetti, G.3
  • 15
    • 84898956615 scopus 로고    scopus 로고
    • Bayesian inference for change points in dynamical systems with reusable states - A Chinese restaurant process approach
    • Florian Stimberg,Manfred Opper, and Andreas Ruttor. Bayesian inference for change points in dynamical systems with reusable states - a Chinese restaurant process approach. JMLR WC&P, 22:1117-1124, 2012.
    • (2012) JMLR WC&P , vol.22 , pp. 1117-1124
    • Stimberg, F.1    Opper, M.2    Ruttor, A.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.