Nir Friedman

ORCID

Publication Activity (10 Years)

Years Active: 1994-2019
Publications (10 Years): 2

Top Venues

Publications

Mor Nitzan, Nikos Karaiskos, Nir Friedman, Nikolaus Rajewsky
Gene expression cartography. Nat. 576 (7785) (2019)
Nili Tickotsky, Tal Sagiv, Jaime Prilusky, Eric Shifrut, Nir Friedman
McPAS-TCR: a manually curated catalogue of pathology-associated T cell receptor sequences. Bioinform. 33 (18) (2017)
Niclas Thomas, Katharine Best, Mattia Cinelli, Shlomit Reich-Zeliger, Hilah Gal, Eric Shifrut, Asaf Madi, Nir Friedman, John Shawe-Taylor, Benny Chain
Tracking global changes induced in the CD4 T-cell receptor repertoire by immunization with a complex antigen using short stretches of CDR3 protein sequence. Bioinform. 30 (22) (2014)
Nir Friedman, Daphne Koller
Being Bayesian about Network Structure CoRR (2013)
Nir Friedman, Dan Geiger, Noam Lotner
Likelihood Computations Using Value Abstractions CoRR (2013)
Nir Friedman, Zohar Yakhini
On the Sample Complexity of Learning Bayesian Networks CoRR (2013)
Nir Friedman, Ori Mosenzon, Noam Slonim, Naftali Tishby
Multivariate Information Bottleneck CoRR (2013)
Craig Boutilier, Nir Friedman, Moisés Goldszmidt, Daphne Koller
Context-Specific Independence in Bayesian Networks CoRR (2013)
Nir Friedman, Stuart J. Russell
Image Segmentation in Video Sequences: A Probabilistic Approach CoRR (2013)
Nir Friedman, Iftach Nachman
Gaussian Process Networks CoRR (2013)
Nir Friedman, Iftach Nachman, Dana Pe'er
Learning Bayesian Network Structure from Massive Datasets: The "Sparse Candidate" Algorithm CoRR (2013)
Nir Friedman, Moisés Goldszmidt
Learning Bayesian Networks with Local Structure CoRR (2013)
Gal Elidan, Nir Friedman
Learning the Dimensionality of Hidden Variables CoRR (2013)
Nir Friedman
The Bayesian Structural EM Algorithm CoRR (2013)
Nir Friedman, Joseph Y. Halpern
Plausibility Measures: A User's Guide CoRR (2013)
Xavier Boyen, Nir Friedman, Daphne Koller
Discovering the Hidden Structure of Complex Dynamic Systems CoRR (2013)
Nir Friedman, Moisés Goldszmidt, Abraham J. Wyner
Data Analysis with Bayesian Networks: A Bootstrap Approach CoRR (2013)
Nir Friedman, Kevin P. Murphy, Stuart J. Russell
Learning the Structure of Dynamic Probabilistic Networks CoRR (2013)
Nir Friedman, Joseph Y. Halpern
A Qualitative Markov Assumption and its Implications for Belief Change CoRR (2013)
Richard Dearden, Nir Friedman, David Andre
Model-Based Bayesian Exploration CoRR (2013)
Nir Friedman, Moisés Goldszmidt
Sequential Update of Bayesian Network Structure CoRR (2013)
Adnan Darwiche, Nir Friedman
Proceedings of the Eighteenth Conference on Uncertainty in Artificial Intelligence (2002) CoRR (2013)
Tal El-Hay, Nir Friedman
Incorporating Expressive Graphical Models in Variational Approximations: Chain-Graphs and Hidden Variables CoRR (2013)
Ofer Meshi, Ariel Jaimovich, Amir Globerson, Nir Friedman
Convexifying the Bethe Free Energy CoRR (2012)
Yonatan Savir, Nir Waysbort, Yaron E. Antebi, Tsvi Tlusty, Nir Friedman
Balancing speed and accuracy of polyclonal T cell activation: a role for extracellular feedback. BMC Syst. Biol. 6 (2012)
Ido Cohn, Tal El-Hay, Nir Friedman, Raz Kupferman
Mean Field Variational Approximation for Continuous-Time Bayesian Networks CoRR (2012)
Tal El-Hay, Nir Friedman, Raz Kupferman
Gibbs Sampling in Factorized Continuous-Time Markov Processes CoRR (2012)
Gal Elidan, Nir Friedman
The Information Bottleneck EM Algorithm CoRR (2012)
Ariel Jaimovich, Ofer Meshi, Nir Friedman
Template Based Inference in Symmetric Relational Markov Random Fields CoRR (2012)
Tal El-Hay, Nir Friedman, Daphne Koller, Raz Kupferman
Continuous Time Markov Networks. CoRR (2012)
Nir Friedman, Raz Kupferman
Dimension Reduction in Singularly Perturbed Continuous-Time Bayesian Networks. CoRR (2012)
Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller, Nir Friedman
Learning Module Networks CoRR (2012)
Iftach Nachman, Gal Elidan, Nir Friedman
"Ideal Parent" Structure Learning for Continuous Variable Networks CoRR (2012)
Noa Novershtern, Aviv Regev, Nir Friedman
Physical Module Networks: an integrative approach for reconstructing transcription regulation. Bioinform. 27 (13) (2011)
Julia Sivriver, Naomi Habib, Nir Friedman
An integrative clustering and modeling algorithm for dynamical gene expression data. Bioinform. 27 (13) (2011)
Tal El-Hay, Ido Cohn, Nir Friedman, Raz Kupferman
Continuous-Time Belief Propagation. ICML (2010)
Ido Cohn, Tal El-Hay, Nir Friedman, Raz Kupferman
Mean Field Variational Approximation for Continuous-Time Bayesian Networks. J. Mach. Learn. Res. 11 (2010)
Ariel Jaimovich, Ruty Rinott, Maya Schuldiner, Hanah Margalit, Nir Friedman
Modularity and directionality in genetic interaction maps. Bioinform. 26 (12) (2010)
Manuel Garber, Mitchell Guttman, Michele E. Clamp, Michael C. Zody, Nir Friedman, Xiaohui Xie
Identifying novel constrained elements by exploiting biased substitution patterns. Bioinform. 25 (12) (2009)
Ofer Meshi, Ariel Jaimovich, Amir Globerson, Nir Friedman
Convexifying the Bethe Free Energy. UAI (2009)
Ido Cohn, Tal El-Hay, Nir Friedman, Raz Kupferman
Mean Field Variational Approximation for Continuous-Time Bayesian Networks. UAI (2009)
Tal El-Hay, Nir Friedman, Raz Kupferman
Gibbs Sampling in Factorized Continuous-Time Markov Processes. UAI (2008)
Helman I. Stern, Ofer Hadar, Nir Friedman
Optimal video stream multiplexing through linear programming. Signal Process. Image Commun. 23 (3) (2008)
Moran Yassour, Tommy Kaplan, Ariel Jaimovich, Nir Friedman
Nucleosome positioning from tiling microarray data. ISMB (2008)
Naomi Habib, Tommy Kaplan, Hanah Margalit, Nir Friedman
A Novel Bayesian DNA Motif Comparison Method for Clustering and Retrieval. PLoS Comput. Biol. 4 (2) (2008)
Gal Elidan, Iftach Nachman, Nir Friedman
"Ideal Parent" Structure Learning for Continuous Variable Bayesian Networks. J. Mach. Learn. Res. 8 (2007)
Matan Ninio, Eyal Privman, Tal Pupko, Nir Friedman
Phylogeny reconstruction: increasing the accuracy of pairwise distance estimation using Bayesian inference of evolutionary rates. Bioinform. 23 (2) (2007)
Ilan Wapinski, Avi Pfeffer, Nir Friedman, Aviv Regev
Automatic genome-wide reconstruction of phylogenetic gene trees. ISMB/ECCB (Supplement of Bioinformatics) (2007)
Ariel Jaimovich, Ofer Meshi, Nir Friedman
Template Based Inference in Symmetric Relational Markov Random Fields. UAI (2007)
Nir Friedman, Raz Kupferman
Dimension Reduction in Singularly Perturbed Continuous-Time Bayesian Networks. UAI (2006)
Tal El-Hay, Nir Friedman, Daphne Koller, Raz Kupferman
Continuous Time Markov Networks. UAI (2006)
Noam Slonim, Nir Friedman, Naftali Tishby
Multivariate Information Bottleneck. Neural Comput. 18 (8) (2006)
Ariel Jaimovich, Gal Elidan, Hanah Margalit, Nir Friedman
Towards an Integrated Protein-Protein Interaction Network: A Relational Markov Network Approach. J. Comput. Biol. 13 (2) (2006)
Gal Elidan, Nir Friedman
Learning Hidden Variable Networks: The Information Bottleneck Approach. J. Mach. Learn. Res. 6 (2005)
Ariel Jaimovich, Gal Elidan, Hanah Margalit, Nir Friedman
Towards an Integrated Protein-Protein Interaction Network. RECOMB (2005)
Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller, Nir Friedman
Learning Module Networks. J. Mach. Learn. Res. 6 (2005)
Itay Mayrose, Nir Friedman, Tal Pupko
A Gamma mixture model better accounts for among site rate heterogeneity. ECCB/JBI (2005)
Tommy Kaplan, Nir Friedman, Hanah Margalit
Predicting Transcription Factor Binding Sites Using Structural Knowledge. RECOMB (2005)
Yoseph Barash, Gal Elidan, Tommy Kaplan, Nir Friedman
Y. Barash, G. Elidan, T. Kaplan, , N. Friedman. Bioinform. 21 (5) (2005)
Tommy Kaplan, Nir Friedman, Hanah Margalit
Ab Initio Prediction of Transcription Factor Targets Using Structural Knowledge. PLoS Comput. Biol. 1 (1) (2005)
Iftach Nachman, Gal Elidan, Nir Friedman
"Ideal Parent" Structure Learning for Continuous Variable Networks. UAI (2004)
Yoseph Barash, Elinor Dehan, Meir Krupsky, Wilbur Franklin, Marc Geraci, Nir Friedman, Naftali Kaminski
Comparative analysis of algorithms for signal quantitation from oligonucleotide microarrays. Bioinform. 20 (6) (2004)
Iftach Nachman, Aviv Regev, Nir Friedman
Inferring quantitative models of regulatory networks from expression data. ISMB/ECCB (Supplement of Bioinformatics) (2004)
Gill Bejerano, Nir Friedman, Naftali Tishby
Efficient Exact p-Value Computation for Small Sample, Sparse, and Surprising Categorical Data. J. Comput. Biol. 11 (5) (2004)
Gal Elidan, Nir Friedman
The Information Bottleneck EM Algorithm. UAI (2003)
Nir Friedman, Joseph Y. Halpern
Modeling Belief in Dynamic Systems, Part I: Foundations CoRR (2003)
Nir Friedman, Daphne Koller
Being Bayesian About Network Structure. A Bayesian Approach to Structure Discovery in Bayesian Networks. Mach. Learn. 50 (1-2) (2003)
Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller, Nir Friedman
Learning Module Networks. UAI (2003)
Yoseph Barash, Gal Elidan, Nir Friedman, Tommy Kaplan
Modeling dependencies in protein-DNA binding sites. RECOMB (2003)
Nir Friedman, Joseph Y. Halpern
Modeling Belief in Dynamic Systems, Part II: Revisions and Update CoRR (2003)
Nir Friedman
Probabilistic models for identifying regulation networks. ECCB (2003)
Lise Getoor, Nir Friedman, Daphne Koller, Benjamin Taskar
Learning Probabilistic Models of Link Structure. J. Mach. Learn. Res. 3 (2002)
Gal Elidan, Matan Ninio, Nir Friedman, Dale Schuurmans
Data Perturbation for Escaping Local Maxima in Learning. AAAI/IAAI (2002)
Nir Friedman, Matan Ninio, Itsik Pe'er, Tal Pupko
A Structural EM Algorithm for Phylogenetic Inference. J. Comput. Biol. 9 (2) (2002)
Yoseph Barash, Nir Friedman
Context-Specific Bayesian Clustering for Gene Expression Data. J. Comput. Biol. 9 (2) (2002)
Eran Segal, Yoseph Barash, Itamar Simon, Nir Friedman, Daphne Koller
From promoter sequence to expression: a probabilistic framework. RECOMB (2002)
Shai Shalev-Shwartz, Shlomo Dubnov, Nir Friedman, Yoram Singer
Robust temporal and spectral modeling for query By melody. SIGIR (2002)
Noam Slonim, Nir Friedman, Naftali Tishby
Unsupervised document classification using sequential information maximization. SIGIR (2002)
Tal Pupko, Itsik Pe'er, Masami Hasegawa, Dan Graur, Nir Friedman
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. Bioinform. 18 (8) (2002)
Nir Friedman, Ori Mosenzon, Noam Slonim, Naftali Tishby
Multivariate Information Bottleneck. UAI (2001)
Dana Pe'er, Aviv Regev, Gal Elidan, Nir Friedman
Inferring subnetworks from perturbed expression profiles. ISMB (Supplement of Bioinformatics) (2001)
Eran Segal, Benjamin Taskar, Audrey P. Gasch, Nir Friedman, Daphne Koller
Rich probabilistic models for gene expression. ISMB (Supplement of Bioinformatics) (2001)
Nir Friedman, Matan Ninio, Itsik Pe'er, Tal Pupko
A structural EM algorithm for phylogenetic inference. RECOMB (2001)
Yoseph Barash, Gill Bejerano, Nir Friedman
A Simple Hyper-Geometric Approach for Discovering Putative Transcription Factor Binding Sites. WABI (2001)
Tal El-Hay, Nir Friedman
Incorporating Expressive Graphical Models in VariationalApproximations: Chain-graphs and Hidden Variables. UAI (2001)
Gal Elidan, Nir Friedman
Learning the Dimensionality of Hidden Variables. UAI (2001)
Noam Slonim, Nir Friedman, Naftali Tishby
Agglomerative Multivariate Information Bottleneck. NIPS (2001)
Yoseph Barash, Nir Friedman
Context-specific Bayesian clustering for gene expression data. RECOMB (2001)
Nir Friedman, Joseph Y. Halpern
Plausibility measures and default reasoning. J. ACM 48 (4) (2001)
Nir Friedman, Joseph Y. Halpern
Belief Revision: A Critique CoRR (2001)
Ronen I. Brafman, Nir Friedman
On decision-theoretic foundations for defaults. Artif. Intell. 133 (1-2) (2001)
Amir Ben-Dor, Nir Friedman, Zohar Yakhini
Class discovery in gene expression data. RECOMB (2001)
Lise Getoor, Nir Friedman, Daphne Koller, Benjamin Taskar
Learning Probabilistic Models of Relational Structure. ICML (2001)
Amir Ben-Dor, Laurakay Bruhn, Nir Friedman, Iftach Nachman, Michèl Schummer, Zohar Yakhini
Tissue classification with gene expression profiles. RECOMB (2000)
Nir Friedman, Dan Geiger, Noam Lotner
Likelihood Computations Using Value Abstraction. UAI (2000)
Gal Elidan, Noam Lotner, Nir Friedman, Daphne Koller
Discovering Hidden Variables: A Structure-Based Approach. NIPS (2000)
Nir Friedman, Joseph Y. Halpern, Daphne Koller
First-order conditional logic for default reasoning revisited. ACM Trans. Comput. Log. 1 (2) (2000)
Nir Friedman, Michal Linial, Iftach Nachman, Dana Pe'er
Using Bayesian Networks to Analyze Expression Data. J. Comput. Biol. 7 (3-4) (2000)
Amir Ben-Dor, Laurakay Bruhn, Nir Friedman, Iftach Nachman, Michèl Schummer, Zohar Yakhini
Tissue Classification with Gene Expression Profiles. J. Comput. Biol. 7 (3-4) (2000)
Nir Friedman, Michal Linial, Iftach Nachman, Dana Pe'er
Using Bayesian networks to analyze expression data. RECOMB (2000)

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Publication Activity (10 Years)

Top Topics

Top Venues

Nir Friedman