Nir Friedman

According to our database1, Nir Friedman authored at least 100 papers between 1994 and 2017.

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Bibliography

2017
McPAS-TCR: a manually curated catalogue of pathology-associated T cell receptor sequences.
Bioinformatics, 2017

2014
Tracking global changes induced in the CD4 T-cell receptor repertoire by immunization with a complex antigen using short stretches of CDR3 protein sequence.
Bioinformatics, 2014

2012
Balancing speed and accuracy of polyclonal T cell activation: a role for extracellular feedback.
BMC Systems Biology, 2012

2011
An integrative clustering and modeling algorithm for dynamical gene expression data.
Bioinformatics [ISMB/ECCB], 2011

Physical Module Networks: an integrative approach for reconstructing transcription regulation.
Bioinformatics [ISMB/ECCB], 2011

2010
Modularity and directionality in genetic interaction maps.
Bioinformatics [ISMB], 2010

Continuous-Time Belief Propagation.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

2009
Identifying novel constrained elements by exploiting biased substitution patterns.
Bioinformatics, 2009

Convexifying the Bethe Free Energy.
Proceedings of the UAI 2009, 2009

Mean Field Variational Approximation for Continuous-Time Bayesian Networks.
Proceedings of the UAI 2009, 2009

Probabilistic Graphical Models - Principles and Techniques.
MIT Press, ISBN: 978-0-262-01319-2, 2009

2008
Optimal video stream multiplexing through linear programming.
Sig. Proc.: Image Comm., 2008

A Novel Bayesian DNA Motif Comparison Method for Clustering and Retrieval.
PLoS Computational Biology, 2008

Gibbs Sampling in Factorized Continuous-Time Markov Processes.
Proceedings of the UAI 2008, 2008

Nucleosome positioning from tiling microarray data.
Proceedings of the Proceedings 16th International Conference on Intelligent Systems for Molecular Biology (ISMB), 2008

2007
"Ideal Parent" Structure Learning for Continuous Variable Bayesian Networks.
Journal of Machine Learning Research, 2007

Phylogeny reconstruction: increasing the accuracy of pairwise distance estimation using Bayesian inference of evolutionary rates.
Bioinformatics, 2007

Template Based Inference in Symmetric Relational Markov Random Fields.
Proceedings of the UAI 2007, 2007

Automatic genome-wide reconstruction of phylogenetic gene trees.
Proceedings of the Proceedings 15th International Conference on Intelligent Systems for Molecular Biology (ISMB) & 6th European Conference on Computational Biology (ECCB), 2007

2006
Multivariate Information Bottleneck.
Neural Computation, 2006

Towards an Integrated Protein-Protein Interaction Network: A Relational Markov Network Approach.
Journal of Computational Biology, 2006

Dimension Reduction in Singularly Perturbed Continuous-Time Bayesian Networks.
Proceedings of the UAI '06, 2006

Continuous Time Markov Networks.
Proceedings of the UAI '06, 2006

2005
Ab Initio Prediction of Transcription Factor Targets Using Structural Knowledge.
PLoS Computational Biology, 2005

Learning Hidden Variable Networks: The Information Bottleneck Approach.
Journal of Machine Learning Research, 2005

Y. Barash, G. Elidan, T. Kaplan, , N. Friedman.
Bioinformatics, 2005

Predicting Transcription Factor Binding Sites Using Structural Knowledge.
Proceedings of the Research in Computational Molecular Biology, 2005

Towards an Integrated Protein-Protein Interaction Network.
Proceedings of the Research in Computational Molecular Biology, 2005

A Gamma mixture model better accounts for among site rate heterogeneity.
Proceedings of the ECCB/JBI'05 Proceedings, Fourth European Conference on Computational Biology/Sixth Meeting of the Spanish Bioinformatics Network (Jornadas de BioInformática), Palacio de Congresos, Madrid, Spain, September 28, 2005

2004
Efficient Exact p-Value Computation for Small Sample, Sparse, and Surprising Categorical Data.
Journal of Computational Biology, 2004

Comparative analysis of algorithms for signal quantitation from oligonucleotide microarrays.
Bioinformatics, 2004

"Ideal Parent" Structure Learning for Continuous Variable Networks.
Proceedings of the UAI '04, 2004

Inferring quantitative models of regulatory networks from expression data.
Proceedings of the Proceedings Twelfth International Conference on Intelligent Systems for Molecular Biology/Third European Conference on Computational Biology 2004, 2004

2003
Being Bayesian About Network Structure. A Bayesian Approach to Structure Discovery in Bayesian Networks.
Machine Learning, 2003

Learning Module Networks.
Proceedings of the UAI '03, 2003

The Information Bottleneck EM Algorithm.
Proceedings of the UAI '03, 2003

Modeling dependencies in protein-DNA binding sites.
Proceedings of the Sventh Annual International Conference on Computational Biology, 2003

Probabilistic models for identifying regulation networks.
Proceedings of the European Conference on Computational Biology (ECCB 2003), 2003

2002
Learning Probabilistic Models of Link Structure.
Journal of Machine Learning Research, 2002

A branch-and-bound algorithm for the inference of ancestral amino-acid sequences when the replacement rate varies among sites: Application to the evolution of five gene families.
Bioinformatics, 2002

Unsupervised document classification using sequential information maximization.
Proceedings of the SIGIR 2002: Proceedings of the 25th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2002

Robust temporal and spectral modeling for query By melody.
Proceedings of the SIGIR 2002: Proceedings of the 25th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2002

From promoter sequence to expression: a probabilistic framework.
Proceedings of the Sixth Annual International Conference on Computational Biology, 2002

Data Perturbation for Escaping Local Maxima in Learning.
Proceedings of the Eighteenth National Conference on Artificial Intelligence and Fourteenth Conference on Innovative Applications of Artificial Intelligence, July 28, 2002

2001
A Simple Hyper-Geometric Approach for Discovering Putative Transcription Factor Binding Sites.
Proceedings of the Algorithms in Bioinformatics, First International Workshop, 2001

Multivariate Information Bottleneck.
Proceedings of the UAI '01: Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence, 2001

Learning the Dimensionality of Hidden Variables.
Proceedings of the UAI '01: Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence, 2001

Incorporating Expressive Graphical Models in VariationalApproximations: Chain-graphs and Hidden Variables.
Proceedings of the UAI '01: Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence, 2001

A structural EM algorithm for phylogenetic inference.
Proceedings of the Fifth Annual International Conference on Computational Biology, 2001

Class discovery in gene expression data.
Proceedings of the Fifth Annual International Conference on Computational Biology, 2001

Context-specific Bayesian clustering for gene expression data.
Proceedings of the Fifth Annual International Conference on Computational Biology, 2001

Agglomerative Multivariate Information Bottleneck.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Rich probabilistic models for gene expression.
Proceedings of the Ninth International Conference on Intelligent Systems for Molecular Biology, 2001

Inferring subnetworks from perturbed expression profiles.
Proceedings of the Ninth International Conference on Intelligent Systems for Molecular Biology, 2001

Learning Probabilistic Models of Relational Structure.
Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001

2000
First-order conditional logic for default reasoning revisited.
ACM Trans. Comput. Log., 2000

Gaussian Process Networks.
Proceedings of the UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30, 2000

Being Bayesian about Network Structure.
Proceedings of the UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30, 2000

Likelihood Computations Using Value Abstraction.
Proceedings of the UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30, 2000

Using Bayesian networks to analyze expression data.
Proceedings of the Fourth Annual International Conference on Computational Molecular Biology, 2000

Tissue classification with gene expression profiles.
Proceedings of the Fourth Annual International Conference on Computational Molecular Biology, 2000

Discovering Hidden Variables: A Structure-Based Approach.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

1999
Modeling Belief in Dynamic Systems, Part II: Revision and Update.
J. Artif. Intell. Res., 1999

Learning Bayesian Network Structure from Massive Datasets: The "Sparse Candidate" Algorithm.
Proceedings of the UAI '99: Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence, Stockholm, Sweden, July 30, 1999

Data Analysis with Bayesian Networks: A Bootstrap Approach.
Proceedings of the UAI '99: Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence, Stockholm, Sweden, July 30, 1999

Model based Bayesian Exploration.
Proceedings of the UAI '99: Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence, Stockholm, Sweden, July 30, 1999

Discovering the Hidden Structure of Complex Dynamic Systems.
Proceedings of the UAI '99: Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence, Stockholm, Sweden, July 30, 1999

Plausibility Measures and Default Reasoning: An Overview.
Proceedings of the 14th Annual IEEE Symposium on Logic in Computer Science, 1999

Learning Probabilistic Relational Models.
Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, 1999

On the application of the bootstrap for computing confidence measures on features of induced Bayesian networks.
Proceedings of the Seventh International Workshop on Artificial Intelligence and Statistics, 1999

Efficient learning using constrained sufficient statistics.
Proceedings of the Seventh International Workshop on Artificial Intelligence and Statistics, 1999

1998
Learning the Structure of Dynamic Probabilistic Networks.
Proceedings of the UAI '98: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, 1998

The Bayesian Structural EM Algorithm.
Proceedings of the UAI '98: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, 1998

Efficient Bayesian Parameter Estimation in Large Discrete Domains.
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Bayesian Network Classification with Continuous Attributes: Getting the Best of Both Discretization and Parametric Fitting.
Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), 1998

Structured Representation of Complex Stochastic Systems.
Proceedings of the Fifteenth National Conference on Artificial Intelligence and Tenth Innovative Applications of Artificial Intelligence Conference, 1998

Bayesian Q-Learning.
Proceedings of the Fifteenth National Conference on Artificial Intelligence and Tenth Innovative Applications of Artificial Intelligence Conference, 1998

Belief Revision with Unreliable Observations.
Proceedings of the Fifteenth National Conference on Artificial Intelligence and Tenth Innovative Applications of Artificial Intelligence Conference, 1998

1997
Bayesian Network Classifiers.
Machine Learning, 1997

Modeling Belief in Dynamic Systems, Part I: Foundations.
Artif. Intell., 1997

Image Segmentation in Video Sequences: A Probabilistic Approach.
Proceedings of the UAI '97: Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, 1997

Sequential Update of Bayesian Network Structure.
Proceedings of the UAI '97: Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, 1997

Generalized Prioritized Sweeping.
Proceedings of the Advances in Neural Information Processing Systems 10, 1997

Challenge: What is the Impact of Bayesian Networks on Learning?
Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, 1997

Learning Belief Networks in the Presence of Missing Values and Hidden Variables.
Proceedings of the Fourteenth International Conference on Machine Learning (ICML 1997), 1997

1996
On the Sample Complexity of Learning Bayesian Networks.
Proceedings of the UAI '96: Proceedings of the Twelfth Annual Conference on Uncertainty in Artificial Intelligence, 1996

A Qualitative Markov Assumption and Its Implications for Belief Change.
Proceedings of the UAI '96: Proceedings of the Twelfth Annual Conference on Uncertainty in Artificial Intelligence, 1996

Learning Bayesian Networks with Local Structure.
Proceedings of the UAI '96: Proceedings of the Twelfth Annual Conference on Uncertainty in Artificial Intelligence, 1996

Context-Specific Independence in Bayesian Networks.
Proceedings of the UAI '96: Proceedings of the Twelfth Annual Conference on Uncertainty in Artificial Intelligence, 1996

Belief Revision: A Critique.
Proceedings of the Fifth International Conference on Principles of Knowledge Representation and Reasoning (KR'96), 1996

Discretizing Continuous Attributes While Learning Bayesian Networks.
Proceedings of the Machine Learning, 1996

First-Order Conditional Logic Revisited.
Proceedings of the Thirteenth National Conference on Artificial Intelligence and Eighth Innovative Applications of Artificial Intelligence Conference, 1996

Plausibility Measures and Default Reasoning.
Proceedings of the Thirteenth National Conference on Artificial Intelligence and Eighth Innovative Applications of Artificial Intelligence Conference, 1996

Building Classifiers Using Bayesian Networks.
Proceedings of the Thirteenth National Conference on Artificial Intelligence and Eighth Innovative Applications of Artificial Intelligence Conference, 1996

1995
Plausibility Measures: A User's Guide.
Proceedings of the UAI '95: Proceedings of the Eleventh Annual Conference on Uncertainty in Artificial Intelligence, 1995

On Decision-Theoretic Foundations for Defaults.
Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, 1995

1994
A Knowledge-Based Framework for Belief change, Part I: Foundations.
Proceedings of the 5th Conference on Theoretical Aspects of Reasoning about Knowledge, 1994

On the Complexity of Conditional Logics.
Proceedings of the 4th International Conference on Principles of Knowledge Representation and Reasoning (KR'94). Bonn, 1994

A Knowledge-Based Framework for Belief Change, Part II: Revision and Update.
Proceedings of the 4th International Conference on Principles of Knowledge Representation and Reasoning (KR'94). Bonn, 1994

Conditional Logics of Belief Change.
Proceedings of the 12th National Conference on Artificial Intelligence, Seattle, WA, USA, July 31, 1994


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