Neil Lawrence's Publications
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2017
Technical Reports
Manifold Alignment Determination: finding correspondences across different data views
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2016
Journal Papers
Detecting periodicities with Gaussian processes
in PeerJ Computer Science 4, pp 0-0
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Variational Inference for Latent Variables and Uncertain Inputs in Gaussian Processes
in Journal of Machine Learning Research 17
[abs]
Conference Papers
Recurrent Gaussian Processes
in Proceedings of the International Conference on Learning Representations (, , eds)
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GLASSES: Relieving The Myopia Of Bayesian Optimisation
in Proceedings of the Nineteenth International Workshop on Artificial Intelligence and Statistics (, eds), pp 790-799
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Chained Gaussian Processes
in Proceedings of the Nineteenth International Workshop on Artificial Intelligence and Statistics (, eds), pp 1431-1440
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Batch Bayesian Optimization via Local Penalization
in Proceedings of the Nineteenth International Workshop on Artificial Intelligence and Statistics (, eds), pp 648-657
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Variationally Auto-Encoded Deep Gaussian Processes
in Proceedings of the International Conference on Learning Representations (, , eds)
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Technical Reports
2015
Journal Papers
Genome-wide modeling of transcription kinetics reveals patterns of RNA production delays
in Proc. Natl. Acad. Sci. USA 112 (42), pp 13115-13120
[abs] [Download PDF]
A reverse-engineering approach to dissect post-translational modulators of transcription factor’s activity from transcriptional data
in BMC Bioinformatics 16 (279)
[abs]
Conference Papers
Semi-described and semi-supervised learning with Gaussian processes
in 31st Conference on Uncertainty in Artificial Intelligence (UAI)
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2014
Journal Papers
Consistent mapping of government malaria records across a changing territory delimitation
in Malaria Journal 13 (Suppl 1)
[abs]
Time-frequency Analysis as Probabilistic Inference
in IEEE Transactions on Signal Processing 62 (23), pp 6171-6181
[abs]
Inference of RNA Polymerase II Transcription Dynamics from Chromatin Immunoprecipitation Time Course Data
in PLoS Computat Biol 10 (5), pp 0-0
[abs]
Fast nonparametric clustering of structured time-series
in IEEE Transactions on Pattern Analysis and Machine Intelligence
[abs]
Warped linear mixed models for the genetic analysis of transformed phenotypes
in Nature Communications 5 (4890)
[abs] [Download Software]
Variational Inference for Uncertainty on the Inputs of Gaussian Process Models
in ar{X}iv preprint ar{X}iv:1409.2287
[abs]
Conference Papers
Malaria surveillance with multiple data sources using Gaussian process models
in 1st International Conference on the Use of Mobile ICT in Africa
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Metrics for Probabilistic Geometries
in Uncertainty in Artificial Intelligence (, eds), pp 800-808
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Tilted Variational Bayes
in Proceedings of the Seventeenth International Workshop on Artificial Intelligence and Statistics (, eds), pp 356-364
Hybrid Discriminative-Generative Approaches with Gaussian Processes
in Proceedings of the Seventeenth International Workshop on Artificial Intelligence and Statistics (, eds), pp 47-56
Technical Reports
Miscellaneous
2013
Journal Papers
Linear Latent Force Models Using Gaussian Processes
in IEEE Transactions on Pattern Analysis and Machine Intelligence 35 (11), pp 2693-2705
Hierarchical Bayesian modelling of gene expression time series across irregularly sampled replicates and clusters
in BMC Bioinformatics 14 (252)
[abs]
Detecting Regulatory Gene-Environment Interactions with Unmeasured Environmental Factors
in Bioinformatics 29 (11), pp 1382-1389
[abs]
Unravelling the enigma of selective vulnerability in neurodegeneration: motor neurons resistant to degeneration in ALS show distinct gene expression characteristics and decreased susceptibility to excitotoxicity
in Acta Neuropathologica 125 (1)
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Conference Papers
Deep Gaussian Processes
in Proceedings of the Sixteenth International Workshop on Artificial Intelligence and Statistics (, eds), pp 207-215
Gaussian Processes for Big Data
in Uncertainty in Artificial Intelligence (, eds)
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Book Chapters
Mining Regulatory Network Connections by Ranking Transcription Factor Target Genes Using Time Series Expression Data
in Data Mining for Systems Biology (, , eds)
[abs]
2012
Journal Papers
Identifying Targets of Multiple Co-regulated Transcription Factors from Expression Time-series by Bayesian Model Comparison
in BMC Systems Biology 6 (53)
[abs]
Modeling Meiotic Chromosomes Indicates a Size Dependent Contribution of Telomere Clustering and Chromosome Rigidity to Homologue Juxtaposition
in PLoS Computat Biol 8 (5), pp 0-0
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Improved linear mixed models for genome-wide association studies
in Nature Methods 9, pp 525-526
[abs]
A Unifying Probabilistic Perspective for Spectral Dimensionality Reduction: Insights and New Models
in Journal of Machine Learning Research 13
Joint Modelling of Confounding Factors and Prominent Genetic Regulators Provides Increased Accuracy in Genetical Genomics Studies
in PLoS Computat Biol 8, pp 0-0
Genome-wide occupancy links Hoxa2 to Wnt-$\beta$-catenin signaling in mouse embryonic development
in Nucleaic Acids Research 40 (9), pp 3390-4001
[abs]
Kernels for Vector-Valued Functions: A Review
in Foundations and Trends in Machine Learning 4 (3), pp 195-266
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Conference Papers
Residual Component Analysis
in Proceedings of the International Conference in Machine Learning (, eds)
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Fast variational inference in the Conjugate Exponential family
in Advances in Neural Information Processing Systems (, , , , eds)
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Manifold Relevance Determination
in Proceedings of the International Conference in Machine Learning (, eds)
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Technical Reports
2011
Journal Papers
Computationally Efficient Convolved Multiple Output Gaussian Processes
in Journal of Machine Learning Research 12, pp 1425-1466
Demodulation as Probabilistic Inference
in IEEE Transactions on Audio, Speech, and Language Processing 19 (), pp 2398-2411
[abs]
Overlapping Mixtures of Gaussian Processes for the Data Association Problem
in Pattern Recognition 10 (4)
[abs]
A Simple Approach to Ranking Differentially Expressed Gene Expression Time Courses through Gaussian Process Regression
in BMC Bioinformatics 12 (180)
tigre: Transcription factor inference through Gaussian process reconstruction of expression for Bioconductor
in Bioinformatics 27, pp 1026-1027
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Conference Papers
Efficient Inference in Matrix-Variate Gaussian Models with i.i.d. Observation Noise
in Neural Information Processing Systems
[abs]
Spectral Dimensionality Reduction via Maximum Entropy
in Proceedings of the Fourteenth International Workshop on Artificial Intelligence and Statistics (, eds), pp 51-59
Variational Gaussian Process Dynamical Systems
in Advances in Neural Information Processing Systems (, , , eds)
[abs][Download PDF] [Download Software] [Supplementary Videos]
Book Chapters
Markov chain Monte Carlo algorithms for Gaussian processes
in Chapter 14 of Bayesian Time Series Models (, , eds)
[abs]
Gaussian Process Inference for Differential Equation Models of Transcriptional Regulation
in Chapter 19 of Handbook of Statistical Systems Biology (, , eds), pp 376-394
[abs]
Technical Reports
Accurate modeling of confounding variation in eQTL studies leads to a great increase in power to detect trans-regulatory effects
[abs]
2010
Journal Papers
Model-based Method for Transcription Factor Target Identification with Limited Data
in Proc. Natl. Acad. Sci. USA 107 (17), pp 7793-7798
[abs] [Download Software]
Elementary properties of CaV1.3 Ca2+ channels expressed in mouse cochlear inner hair cells
in The Journal of Physiology 588, pp 187-189
[abs]
TFInfer: a tool for probabilistic inference of transcription factor activities
in Bioinformatics 26, pp 2635-2636
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Conference Papers
Bayesian Gaussian Process Latent Variable Model
in Proceedings of the Thirteenth International Workshop on Artificial Intelligence and Statistics (, eds), pp 844-851
Switched Latent Force Models for Movement Segmentation
in Advances in Neural Information Processing Systems (, , , , eds), pp 55-63
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Efficient Multioutput Gaussian Processes through Variational Inducing Kernels
in Proceedings of the Thirteenth International Workshop on Artificial Intelligence and Statistics (, eds), pp 25-32
Book Chapters
Introduction to Learning and Inference in Computational Systems Biology
in Chapter 1 of Learning and Inference in Computational Systems Biology (, , , eds)
[abs]
Gaussian Processes for Missing Species in Biochemical Systems
in Chapter 9 of Learning and Inference in Computational Systems Biology (, , , eds)
[abs]
A Brief Introduction to Bayesian Inference
in Chapter 5 of Learning and Inference in Computational Systems Biology (, , , eds)
[abs]
Technical Reports
A Unifying Probabilistic Perspective for Spectral Dimensionality Reduction
2009
Journal Papers
puma: a Bioconductor package for Propagating Uncertainty in Microarray Analysis
in BMC Bioinformatics 10 (211)
[abs]
Conference Papers
Efficient Sampling for Gaussian Process Inference using Control Variables
in Advances in Neural Information Processing Systems (, , , eds), pp 1681-1688
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Non-Linear Matrix Factorization with Gaussian Processes
in Proceedings of the International Conference in Machine Learning (, eds)
Backing Off: Hierarchical Decomposition of Activity for 3D Novel Pose Recovery
in British Machine Vision Conference
Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes
in Advances in Neural Information Processing Systems (, , , eds), pp 217-224
[abs]
Latent Force Models
in Proceedings of the Twelfth International Workshop on Artificial Intelligence and Statistics (, eds), pp 9-16
Sparse Convolved Gaussian Processes for Multi-output Regression
in Advances in Neural Information Processing Systems (, , , eds), pp 57-64
Technical Reports
Variational Inducing Kernels for Sparse Convolved Multiple Output Gaussian Processes
[abs][Download PDF]
2008
Journal Papers
Probabilistic approach to detecting dependencies between data sets
in Neurocomputing 72, pp 39-46
[abs]
Gaussian Process Modelling of Latent Chemical Species: Applications to Inferring Transcription Factor Activities
in Bioinformatics 24, pp 0-0
Conference Papers
Topologically-Constrained Latent Variable Models
in Proceedings of the International Conference in Machine Learning (, eds), pp 1080-1087
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Gaussian Process Latent Variable Models For Human Pose Estimation
in Machine Learning for Multimodal Interaction (MLMI 2007) (, , eds), pp 132-143
Ambiguity Modeling in Latent Spaces
in Machine Learning for Multimodal Interaction (MLMI 2008) (, eds), pp 62-73
2007
Conference Papers
Model-driven detection of Clean Speech Patches in Noise
in Proceedings of Interspeech 2007
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Modelling transcriptional regulation using Gaussian Processes
in Advances in Neural Information Processing Systems (, , eds), pp 785-792
Learning for Larger Datasets with the Gaussian Process Latent Variable Model
in Proceedings of the Eleventh International Workshop on Artificial Intelligence and Statistics (, eds), pp 243-250
Hierarchical Gaussian Process Latent Variable Models
in Proceedings of the International Conference in Machine Learning ( ed.), pp 481-488
WiFi-SLAM Using Gaussian Process Latent Variable Models
in Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI 2007) ( ed.), pp 2480-2485
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Gaussian Process Latent Variable Models for Fault Detection
in Computational Intelligence and Data Mining, pp 287-292
[abs]
Miscellaneous
2006
Journal Papers
Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis
in Journal of Machine Learning Research 7, pp 455-491
Probabilistic inference of transcription factor concentrations and gene-specific regulatory activities
in Bioinformatics 22 (22), pp 2275-2281
A probabilistic dynamical model for quantitative inference of the regulatory mechanism of transcription
in Bioinformatics 22 (14), pp 1753-1759
[abs][Download PDF] [Download Software] [Supplementary Material]
Propagating Uncertainty in Microarray Data Analysis
in Briefings in Bioinformatics 7 (1), pp 37-47
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Probe-level Measurement Error Improves Accuracy in Detecting Differential Gene Expression
in Bioinformatics 22 (17), pp 2107-2113
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Conference Papers
Identifying submodules of cellular regulatory networks
in International Conference on Computational Methods in Systems Biology
[abs]
Local Distance Preservation in the GP-LVM through Back Constraints
in Proceedings of the International Conference in Machine Learning (, eds), pp 513-520
Fast Variational Inference for Gaussian Process Models through KL-Correction
in ECML, Berlin, 2006, pp 270-281
Book Chapters
Technical Reports
Large Scale Learning with the Gaussian Process Latent Variable Model
2005
Journal Papers
Probabilistic Non-linear Principal Component Analysis with Gaussian Process Latent Variable Models
in Journal of Machine Learning Research 6, pp 1783-1816
[abs] [C++ Software][MATLAB Software][JMLR PDF][JMLR Abstract]
A Tractable Probabilistic Model for Affymetrix Probe-level Analysis across Multiple Chips
in Bioinformatics 21 (18), pp 3637-3644
[abs][Download PDF] [Download Software] [Advance Access][Pre-print PDF]
Variational inference for Student-$t$ models: Robust Bayesian interpolation and generalised component analysis
in Neurocomputing 69, pp 123-141
Accounting for Probe-level Noise in Principal Component Analysis of Microarray Data
in Bionformatics 21 (19), pp 3748-3754
[abs][Download PDF] [Download Software] [Advance Access][Pre-print PDF][Bioinformatics Abstract]
Conference Papers
A Hybrid MaxEnt/HMM Based ASR System
in Proceedings of Interspeech 2005 --- 9th European Conference on Speech Communication and Technology
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Automatic Determination of the Number of Clusters Using Spectral Algorithms
in Procedings of MLSP'05
Semi-supervised Learning via Gaussian Processes
in Advances in Neural Information Processing Systems (, , eds), pp 753-760
Book Chapters
Technical Reports
Variational Inference in Gaussian Processes via Probabilistic Point Assimilation
[abs] [Download PSGZ] [Software]
Miscellaneous
2004
Journal Papers
Reducing the Variability in cDNA Microarray Image Processing by Bayesian Inference
in Bioinformatics 20 (4), pp 518-526
Conference Papers
Learning to Learn with the Informative Vector Machine
in Proceedings of the International Conference in Machine Learning (, eds), pp 512-519
Gaussian Process Models for Visualisation of High Dimensional Data
in Advances in Neural Information Processing Systems (, , eds), pp 329-336
Acoustic Space Dimensionality Selection and Combination using the Maximum Entropy Principle
in International Conference on Acoustics, Speech and Signal Processing
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Technical Reports
Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis
The Informative Vector Machine: A Practical Probabilistic Alternative to the Support Vector Machine
Probabilistic Non-linear Principal Component Analysis with Gaussian Process Latent Variable Models
2003
Journal Papers
A Probabilistic Model for the Extraction of Expression Levels from Oligonucleotide Arrays
in Biochemical Transations 31 (6), pp 1510-1512
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Conference Papers
Variational Inference for Visual Tracking
in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp 773-780
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A Variational Approach to Robust Bayesian Interpolation
in Neural Networks for Signal Processing XIII (, , , , , eds), pp 229-238
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Fast Forward Selection to Speed Up Sparse Gaussian Process Regression
in Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics (, eds)
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Bayesian Processing of Microarray Images
in Neural Networks for Signal Processing XIII (, , , , , eds), pp 71-80
Fast Sparse Gaussian Process Methods: The Informative Vector Machine
in Advances in Neural Information Processing Systems (, , eds), pp 625-632
Technical Reports
2002
Conference Papers
Optimising Synchronisation Times for Mobile Devices
in Advances in Neural Information Processing Systems (, , eds), pp 1401-1408
[abs] [Download PSGZ]
Technical Reports
2001
Journal Papers
A Comparison of State-of-the-Art Classification Techniques with Application to Cytogenetics
in Neural Computing and Applications 10 (1), pp 39-47
[abs] [Download PSGZ]
Conference Papers
Probabilistic Modelling of Replica Divergence
in Proceedings of the 8th Workshop on Hot Topics in Operating Systems HOTOS (VIII)
[abs][Download PDF] [Download PSGZ]
Node Relevance Determination
in The {XI}th Italian Workshop on Neural Networks (, eds)
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Estimating a Kernel Fisher Discriminant in the Presence of Label Noise
in Proceedings of the International Conference in Machine Learning (, eds)
Variational Learning for Multi-layer networks of Linear Threshold Units
in Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics (, eds), pp 245-252
[abs][Download PDF] [Download PSGZ]
Technical Reports
Miscellaneous
2000
Technical Reports
1999
Technical Reports
1998
Conference Papers
Mixture Representations for Inference and Learning in Boltzmann Machines
in Uncertainty in Artificial Intelligence (, eds), pp 320-327
[abs] [Download PSGZ]
Approximating Posterior Distributions in Belief Networks using Mixtures
in Advances in Neural Information Processing Systems (, , eds), pp 416-422
[abs] [Download PSGZ]
Technical Reports
0001
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