| 2010 | ICML | Continuous-Time Belief Propagation. | Tal El-Hay, Ido Cohn, Nir Friedman, Raz Kupferman |
| 2009 | UAI | Mean Field Variational Approximation for Continuous-Time Bayesian Networks. | Ido Cohn, Tal El-Hay, Nir Friedman, Raz Kupferman |
| 2009 | UAI | Convexifying the Bethe Free Energy. | Ofer Meshi, Ariel Jaimovich, Amir Globerson, Nir Friedman |
| 2008 | ISMB | Nucleosome positioning from tiling microarray data. | Moran Yassour, Tommy Kaplan, Ariel Jaimovich, Nir Friedman |
| 2008 | UAI | Gibbs Sampling in Factorized Continuous-Time Markov Processes. | Tal El-Hay, Nir Friedman, Raz Kupferman |
| 2007 | ISMB | Automatic genome-wide reconstruction of phylogenetic gene trees. | Ilan Wapinski, Avi Pfeffer, Nir Friedman, Aviv Regev |
| 2007 | UAI | Template Based Inference in Symmetric Relational Markov Random Fields. | Ariel Jaimovich, Ofer Meshi, Nir Friedman |
| 2006 | UAI | Continuous Time Markov Networks. | Tal El-Hay, Nir Friedman, Daphne Koller, Raz Kupferman |
| 2006 | UAI | Dimension Reduction in Singularly Perturbed Continuous-Time Bayesian Networks. | Nir Friedman, Raz Kupferman |
| 2005 | ECCB | A Gamma mixture model better accounts for among site rate heterogeneity. | Itay Mayrose, Nir Friedman, Tal Pupko |
| 2005 | RECOMB | Towards an Integrated Protein-Protein Interaction Network. | Ariel Jaimovich, Gal Elidan, Hanah Margalit, Nir Friedman |
| 2005 | RECOMB | Predicting Transcription Factor Binding Sites Using Structural Knowledge. | Tommy Kaplan, Nir Friedman, Hanah Margalit |
| 2004 | ISMB | Inferring quantitative models of regulatory networks from expression data. | Iftach Nachman, Aviv Regev, Nir Friedman |
| 2004 | UAI | "Ideal Parent" Structure Learning for Continuous Variable Networks. | Iftach Nachman, Gal Elidan, Nir Friedman |
| 2003 | ECCB | Probabilistic models for identifying regulation networks. | Nir Friedman |
| 2003 | RECOMB | Modeling dependencies in protein-DNA binding sites. | Yoseph Barash, Gal Elidan, Nir Friedman, Tommy Kaplan |
| 2003 | UAI | The Information Bottleneck EM Algorithm. | Gal Elidan, Nir Friedman |
| 2003 | UAI | Learning Module Networks. | Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller, Nir Friedman |
| 2002 | AAAI | Data Perturbation for Escaping Local Maxima in Learning. | Gal Elidan, Matan Ninio, Nir Friedman, Dale Schuurmans |
| 2002 | RECOMB | From promoter sequence to expression: a probabilistic framework. | Eran Segal, Yoseph Barash, Itamar Simon, Nir Friedman, Daphne Koller |
| 2002 | SIGIR | Robust temporal and spectral modeling for query By melody. | Shai Shalev-Shwartz, Shlomo Dubnov, Nir Friedman, Yoram Singer |
| 2002 | SIGIR | Unsupervised document classification using sequential information maximization. | Noam Slonim, Nir Friedman, Naftali Tishby |
| 2001 | ICML | Learning Probabilistic Models of Relational Structure. | Lise Getoor, Nir Friedman, Daphne Koller, Benjamin Taskar |
| 2001 | ISMB | Inferring subnetworks from perturbed expression profiles. | Dana Pe'er, Aviv Regev, Gal Elidan, Nir Friedman |
| 2001 | ISMB | Rich probabilistic models for gene expression. | Eran Segal, Benjamin Taskar, Audrey P. Gasch, Nir Friedman, Daphne Koller |
| 2001 | RECOMB | Context-specific Bayesian clustering for gene expression data. | Yoseph Barash, Nir Friedman |
| 2001 | RECOMB | Class discovery in gene expression data. | Amir Ben-Dor, Nir Friedman, Zohar Yakhini |
| 2001 | RECOMB | A structural EM algorithm for phylogenetic inference. | Nir Friedman, Matan Ninio, Itsik Pe'er, Tal Pupko |
| 2001 | UAI | Incorporating Expressive Graphical Models in VariationalApproximations: Chain-graphs and Hidden Variables. | Tal El-Hay, Nir Friedman |
| 2001 | UAI | Learning the Dimensionality of Hidden Variables. | Gal Elidan, Nir Friedman |
| 2001 | UAI | Multivariate Information Bottleneck. | Nir Friedman, Ori Mosenzon, Noam Slonim, Naftali Tishby |
| 2001 | WABI | A Simple Hyper-Geometric Approach for Discovering Putative Transcription Factor Binding Sites. | Yoseph Barash, Gill Bejerano, Nir Friedman |
| 2000 | RECOMB | Tissue classification with gene expression profiles. | Amir Ben-Dor, Laurakay Bruhn, Nir Friedman, Iftach Nachman, Michl Schummer, Zohar Yakhini |
| 2000 | RECOMB | Using Bayesian networks to analyze expression data. | Nir Friedman, Michal Linial, Iftach Nachman, Dana Pe'er |
| 2000 | UAI | Likelihood Computations Using Value Abstraction. | Nir Friedman, Dan Geiger, Noam Lotner |
| 2000 | UAI | Being Bayesian about Network Structure. | Nir Friedman, Daphne Koller |
| 2000 | UAI | Gaussian Process Networks. | Nir Friedman, Iftach Nachman |
| 1999 | AISTATS | Efficient learning using constrained sufficient statistics. | Nir Friedman, Lise Getoor |
| 1999 | AISTATS | On the application of the bootstrap for computing confidence measures on features of induced Bayesian networks. | Nir Friedman, Moiss Goldszmidt, Abraham J. Wyner |
| 1999 | IJCAI | Learning Probabilistic Relational Models. | Nir Friedman, Lise Getoor, Daphne Koller, Avi Pfeffer |
| 1999 | LICS | Plausibility Measures and Default Reasoning: An Overview. | Joseph Y. Halpern, Nir Friedman |
| 1999 | UAI | Discovering the Hidden Structure of Complex Dynamic Systems. | Xavier Boyen, Nir Friedman, Daphne Koller |
| 1999 | UAI | Model based Bayesian Exploration. | Richard Dearden, Nir Friedman, David Andre |
| 1999 | UAI | Data Analysis with Bayesian Networks: A Bootstrap Approach. | Nir Friedman, Moiss Goldszmidt, Abraham J. Wyner |
| 1999 | UAI | Learning Bayesian Network Structure from Massive Datasets: The "Sparse Candidate" Algorithm. | Nir Friedman, Iftach Nachman, Dana Pe'er |
| 1998 | AAAI | Belief Revision with Unreliable Observations. | Craig Boutilier, Nir Friedman, Joseph Y. Halpern |
| 1998 | AAAI | Bayesian Q-Learning. | Richard Dearden, Nir Friedman, Stuart Russell |
| 1998 | AAAI | Structured Representation of Complex Stochastic Systems. | Nir Friedman, Daphne Koller, Avi Pfeffer |
| 1998 | ICML | Bayesian Network Classification with Continuous Attributes: Getting the Best of Both Discretization and Parametric Fitting. | Nir Friedman, Moiss Goldszmidt, Thomas J. Lee |
| 1998 | UAI | The Bayesian Structural EM Algorithm. | Nir Friedman |
| 1998 | UAI | Learning the Structure of Dynamic Probabilistic Networks. | Nir Friedman, Kevin P. Murphy, Stuart Russell |
| 1997 | ICML | Learning Belief Networks in the Presence of Missing Values and Hidden Variables. | Nir Friedman |
| 1997 | IJCAI | Challenge: What is the Impact of Bayesian Networks on Learning? | Nir Friedman, Moiss Goldszmidt, David Heckerman, Stuart Russell |
| 1997 | UAI | Sequential Update of Bayesian Network Structure. | Nir Friedman, Moiss Goldszmidt |
| 1997 | UAI | Image Segmentation in Video Sequences: A Probabilistic Approach. | Nir Friedman, Stuart Russell |
| 1996 | AAAI | Building Classifiers Using Bayesian Networks. | Nir Friedman, Moiss Goldszmidt |
| 1996 | AAAI | Plausibility Measures and Default Reasoning. | Nir Friedman, Joseph Y. Halpern |
| 1996 | AAAI | First-Order Conditional Logic Revisited. | Nir Friedman, Joseph Y. Halpern, Daphne Koller |
| 1996 | ICML | Discretizing Continuous Attributes While Learning Bayesian Networks. | Nir Friedman, Moiss Goldszmidt |
| 1996 | KR | Belief Revision: A Critique. | Nir Friedman, Joseph Y. Halpern |
| 1996 | UAI | Context-Specific Independence in Bayesian Networks. | Craig Boutilier, Nir Friedman, Moiss Goldszmidt, Daphne Koller |
| 1996 | UAI | Learning Bayesian Networks with Local Structure. | Nir Friedman, Moiss Goldszmidt |
| 1996 | UAI | A Qualitative Markov Assumption and Its Implications for Belief Change. | Nir Friedman, Joseph Y. Halpern |
| 1996 | UAI | On the Sample Complexity of Learning Bayesian Networks. | Nir Friedman, Zohar Yakhini |
| 1995 | IJCAI | On Decision-Theoretic Foundations for Defaults. | Ronen I. Brafman, Nir Friedman |
| 1995 | UAI | Plausibility Measures: A User's Guide. | Nir Friedman, Joseph Y. Halpern |
| 1994 | AAAI | Conditional Logics of Belief Change. | Nir Friedman, Joseph Y. Halpern |
| 1994 | KR | A Knowledge-Based Framework for Belief Change, Part II: Revision and Update. | Nir Friedman, Joseph Y. Halpern |
| 1994 | KR | On the Complexity of Conditional Logics. | Nir Friedman, Joseph Y. Halpern |
| 1994 | TARK | A Knowledge-Based Framework for Belief change, Part I: Foundations. | Nir Friedman, Joseph Y. Halpern |