Latent Force Models: Bridging the Divide between Mechanistic and Data Modelling Paradigms
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[1] Neil D. Lawrence,et al. Linear Latent Force Models Using Gaussian Processes , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[2] Bernhard Schölkopf,et al. Switched Latent Force Models for Movement Segmentation , 2010, NIPS.
[3] Antti Honkela,et al. Model-based method for transcription factor target identification with limited data , 2010, Proceedings of the National Academy of Sciences.
[4] Neil D. Lawrence,et al. Efficient Multioutput Gaussian Processes through Variational Inducing Kernels , 2010, AISTATS.
[5] E. Furlong,et al. Combinatorial binding predicts spatio-temporal cis-regulatory activity , 2009, Nature.
[6] Neil D. Lawrence,et al. Latent Force Models , 2009, AISTATS.
[7] Neil D. Lawrence,et al. Sparse Convolved Gaussian Processes for Multi-output Regression , 2008, NIPS.
[8] Neil D. Lawrence,et al. Gaussian process modelling of latent chemical species: applications to inferring transcription factor activities , 2008, ECCB.
[9] D. di Bernardo,et al. Direct targets of the TRP63 transcription factor revealed by a combination of gene expression profiling and reverse engineering. , 2008, Genome research.
[10] M. Barenco,et al. Ranked prediction of p53 targets using hidden variable dynamic modeling , 2006, Genome Biology.
[11] Michael E. Tipping,et al. Probabilistic Principal Component Analysis , 1999 .
[12] Sam T. Roweis,et al. EM Algorithms for PCA and SPCA , 1997, NIPS.