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Neil D. Lawrence: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Guido Sanguinetti, Magnus Rattray, Neil D. Lawrence
    Identifying Submodules of Cellular Regulatory Networks. [Citation Graph (0, 0)][DBLP]
    CMSB, 2006, pp:155-168 [Conf]
  2. Jaco Vermaak, Neil D. Lawrence, Patrick Pérez
    Variational Inference for Visual Tracking. [Citation Graph (0, 0)][DBLP]
    CVPR (1), 2003, pp:773-780 [Conf]
  3. Neil D. Lawrence, John C. Platt, Michael I. Jordan
    Extensions of the Informative Vector Machine. [Citation Graph (0, 0)][DBLP]
    Deterministic and Statistical Methods in Machine Learning, 2004, pp:56-87 [Conf]
  4. Nathaniel J. King, Neil D. Lawrence
    Fast Variational Inference for Gaussian Process Models Through KL-Correction. [Citation Graph (0, 0)][DBLP]
    ECML, 2006, pp:270-281 [Conf]
  5. Guido Sanguinetti, Neil D. Lawrence
    Missing Data in Kernel PCA. [Citation Graph (0, 0)][DBLP]
    ECML, 2006, pp:751-758 [Conf]
  6. Antony I. T. Rowstron, Neil D. Lawrence, Christopher M. Bishop
    Probabilistic Modelling of Replica Divergence. [Citation Graph (0, 0)][DBLP]
    HotOS, 2001, pp:55-60 [Conf]
  7. Neil D. Lawrence, Joaquin Quiñonero Candela
    Local distance preservation in the GP-LVM through back constraints. [Citation Graph (0, 0)][DBLP]
    ICML, 2006, pp:513-520 [Conf]
  8. Neil D. Lawrence, John C. Platt
    Learning to learn with the informative vector machine. [Citation Graph (0, 0)][DBLP]
    ICML, 2004, pp:- [Conf]
  9. Neil D. Lawrence, Bernhard Schölkopf
    Estimating a Kernel Fisher Discriminant in the Presence of Label Noise. [Citation Graph (0, 0)][DBLP]
    ICML, 2001, pp:306-313 [Conf]
  10. Brian Ferris, Dieter Fox, Neil Lawrence
    WiFi-SLAM Using Gaussian Process Latent Variable Models. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2007, pp:2480-2485 [Conf]
  11. Christopher M. Bishop, Neil D. Lawrence, Tommi Jaakkola, Michael I. Jordan
    Approximating Posterior Distributions in Belief Networks Using Mixtures. [Citation Graph (0, 0)][DBLP]
    NIPS, 1997, pp:- [Conf]
  12. Neil D. Lawrence
    Gaussian Process Latent Variable Models for Visualisation of High Dimensional Data. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  13. Neil D. Lawrence, Michael I. Jordan
    Semi-supervised Learning via Gaussian Processes. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  14. Neil D. Lawrence, Antony I. T. Rowstron, Christopher M. Bishop, M. J. Taylor
    Optimising Synchronisation Times for Mobile Devices. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:1401-1408 [Conf]
  15. Neil D. Lawrence, Matthias Seeger, Ralf Herbrich
    Fast Sparse Gaussian Process Methods: The Informative Vector Machine. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:609-616 [Conf]
  16. Neil D. Lawrence, Christopher M. Bishop, Michael I. Jordan
    Mixture Representations for Inference and Learning in Boltzmann Machines. [Citation Graph (0, 0)][DBLP]
    UAI, 1998, pp:320-327 [Conf]
  17. Magnus Rattray, Xuejun Liu, Guido Sanguinetti, Marta Milo, Neil D. Lawrence
    Propagating uncertainty in microarray data analysis. [Citation Graph (0, 0)][DBLP]
    Briefings in Bioinformatics, 2006, v:7, n:1, pp:37-47 [Journal]
  18. Neil D. Lawrence, Marta Milo, Mahesan Niranjan, Penny Rashbass, Stephan Soullier
    Reducing the variability in cDNA microarray image processing by Bayesian inference. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2004, v:20, n:4, pp:- [Journal]
  19. Xuejun Liu, Marta Milo, Neil D. Lawrence, Magnus Rattray
    A tractable probabilistic model for Affymetrix probe-level analysis across multiple chips. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2005, v:21, n:18, pp:3637-3644 [Journal]
  20. Xuejun Liu, Marta Milo, Neil D. Lawrence, Magnus Rattray
    Probe-level measurement error improves accuracy in detecting differential gene expression. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2006, v:22, n:17, pp:2107-2113 [Journal]
  21. Guido Sanguinetti, Marta Milo, Magnus Rattray, Neil D. Lawrence
    Accounting for probe-level noise in principal component analysis of microarray data. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2005, v:21, n:19, pp:3748-3754 [Journal]
  22. Guido Sanguinetti, Magnus Rattray, Neil D. Lawrence
    A probabilistic dynamical model for quantitative inference of the regulatory mechanism of transcription. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2006, v:22, n:14, pp:1753-1759 [Journal]
  23. Guido Sanguinetti, Neil D. Lawrence, Magnus Rattray
    Probabilistic inference of transcription factor concentrations and gene-specific regulatory activities. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2006, v:22, n:22, pp:2775-2781 [Journal]
  24. Michael E. Tipping, Neil D. Lawrence
    Variational inference for Student-t models: Robust Bayesian interpolation and generalised component analysis. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2005, v:69, n:1-3, pp:123-141 [Journal]
  25. Neil D. Lawrence
    Probabilistic Non-linear Principal Component Analysis with Gaussian Process Latent Variable Models. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2005, v:6, n:, pp:1783-1816 [Journal]
  26. Tonatiuh Peña Centeno, Neil D. Lawrence
    Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:455-491 [Journal]
  27. Boaz Lerner, Neil D. Lawrence
    A Comparison of State-of-the-Art Classification Techniques with Application to Cytogenetics. [Citation Graph (0, 0)][DBLP]
    Neural Computing and Applications, 2001, v:10, n:1, pp:39-47 [Journal]
  28. Raquel Urtasun, David J. Fleet, Neil D. Lawrence
    Modeling Human Locomotion with Topologically Constrained Latent Variable Models. [Citation Graph (0, 0)][DBLP]
    Workshop on Human Motion, 2007, pp:104-118 [Conf]
  29. Neil D. Lawrence, Andrew J. Moore
    Hierarchical Gaussian process latent variable models. [Citation Graph (0, 0)][DBLP]
    ICML, 2007, pp:481-488 [Conf]
  30. Neil D. Lawrence, Guido Sanguinetti, Magnus Rattray
    Modelling transcriptional regulation using Gaussian Processes. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:785-792 [Conf]
  31. Luka Eciolaza, M. Alkarouri, Neil D. Lawrence, Visakan Kadirkamanathan, Peter J. Fleming
    Gaussian Process Latent Variable Models for Fault Detection. [Citation Graph (0, 0)][DBLP]
    CIDM, 2007, pp:287-292 [Conf]

  32. Gaussian process modelling of latent chemical species: applications to inferring transcription factor activities. [Citation Graph (, )][DBLP]


  33. Topologically-constrained latent variable models. [Citation Graph (, )][DBLP]


  34. Non-linear matrix factorization with Gaussian processes. [Citation Graph (, )][DBLP]


  35. Gaussian Process Latent Variable Models for Human Pose Estimation. [Citation Graph (, )][DBLP]


  36. Ambiguity Modeling in Latent Spaces. [Citation Graph (, )][DBLP]


  37. Efficient Sampling for Gaussian Process Inference using Control Variables. [Citation Graph (, )][DBLP]


  38. Sparse Convolved Gaussian Processes for Multi-output Regression. [Citation Graph (, )][DBLP]


  39. Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes. [Citation Graph (, )][DBLP]


  40. puma: a Bioconductor package for propagating uncertainty in microarray analysis. [Citation Graph (, )][DBLP]


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