Dan Geiger

18.1k total citations · 3 hit papers
97 papers, 10.5k citations indexed

About

Dan Geiger is a scholar working on Artificial Intelligence, Genetics and Molecular Biology. According to data from OpenAlex, Dan Geiger has authored 97 papers receiving a total of 10.5k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Artificial Intelligence, 27 papers in Genetics and 24 papers in Molecular Biology. Recurrent topics in Dan Geiger's work include Bayesian Modeling and Causal Inference (40 papers), Genetic Associations and Epidemiology (18 papers) and Genetic Mapping and Diversity in Plants and Animals (14 papers). Dan Geiger is often cited by papers focused on Bayesian Modeling and Causal Inference (40 papers), Genetic Associations and Epidemiology (18 papers) and Genetic Mapping and Diversity in Plants and Animals (14 papers). Dan Geiger collaborates with scholars based in Israel, United States and United Kingdom. Dan Geiger's co-authors include David Heckerman, David M. Chickering, Nir Friedman, Moisés Goldszmidt, Judea Pearl, Thomas Verma, Christopher Meek, Omer Weissbrod, Mark Silberstein and Max Chickering and has published in prestigious journals such as Science, Nature Genetics and Bioinformatics.

In The Last Decade

Dan Geiger

97 papers receiving 9.8k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Bayesian Network Classifiers

1997 3.3k citations Nir Friedman, Dan Geiger et al. Machine Learning profile →
Learning Bayesian Networks: The Combination of Knowledge and Statistical Data

1995 2.0k citations David Heckerman, Dan Geiger et al. Machine Learning profile →
Learning Bayesian networks: The combination of knowledge and statistical data

1995 1.5k citations David Heckerman, Dan Geiger et al. Machine Learning profile →

Peers

Countries citing papers authored by Dan Geiger

Since Specialization

Citations

This map shows the geographic impact of Dan Geiger's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Dan Geiger with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Geiger more than expected).

Fields of papers citing papers by Dan Geiger

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dan Geiger. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Dan Geiger. The network helps show where Dan Geiger may publish in the future.

Co-authorship network of co-authors of Dan Geiger

This figure shows the co-authorship network connecting the top 25 collaborators of Dan Geiger. A scholar is included among the top collaborators of Dan Geiger based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Dan Geiger. Dan Geiger is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work	Indexed citations
1	Quantitative analysis of population-scale family trees with millions of relatives 2018 ·Science ·Joanna Kaplanis, Assaf Gordon, Tal Shor, Omer Weissbrod, Dan Geiger, (unknown), (unknown), Barak Markus, Mona A. Sheikh, Melissa Gymrek, Gaurav Bhatia, Daniel G. MacArthur, Alkes L. Price, Yaniv Erlich	131
2	A system for exact and approximate genetic linkage analysis of SNP data in large pedigrees 2013 ·Bioinformatics ·Mark Silberstein, Omer Weissbrod, (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), Adel Shalata, Zvi Borochowitz, Rina Dechter, E. A. Thompson, Dan Geiger	1
3	Admixture Aberration Analysis: Application to Mapping in Admixed Population Using Pooled DNA 2011 ·Journal of Computational Biology ·Sivan Bercovici, Dan Geiger	1
4	Speeding Up HMM Algorithms For Genetic Linkage Analysis 2009 ·Bioinformatics ·Dan Geiger, C. E. Meek, Ydo Wexler	2
5	Alopecia, Neurological Defects, and Endocrinopathy Syndrome Caused by Decreased Expression of RBM28, a Nucleolar Protein Associated with Ribosome Biogenesis 2008 ·The American Journal of Human Genetics ·Janna Nousbeck, Ronen Spiegel, Akemi Ishida‐Yamamoto, Margarita Indelman, Ayelet Shani‐Adir, Noam Adir, E. Lipkin, Sivan Bercovici, Dan Geiger, Maurice A. M. Van Steensel, Peter M. Steijlen, Richard N. Bergman, Albrecht Bindereif, Mordechai Choder, Stavit A. Shalev, Eli Sprecher	55
6	Importance sampling via variational optimization 2007 ·Uncertainty in Artificial Intelligence ·Ydo Wexler, Dan Geiger	4
7	Online System for Faster Multipoint Linkage Analysis via Parallel Execution on Thousands of Personal Computers 2006 ·The American Journal of Human Genetics ·Mark Silberstein, (unknown), (unknown), (unknown), Assaf Schuster, Dan Geiger	66
8	Structured Variational Inference Procedures and their Realizations. 2005 ·International Conference on Artificial Intelligence and Statistics ·Dan Geiger, Christopher Meek	7
9	Identification of a Novel Locus Associated with Congenital Recessive Ichthyosis on 12p11.2–q13 2005 ·Journal of Investigative Dermatology ·(unknown), Dan Geiger, Margarita Indelman, (unknown), Richard N. Bergman, Eli Sprecher	19
10	Automated analytic asymptotic evaluation of the marginal likelihood for latent models 2002 ·Uncertainty in Artificial Intelligence ·(unknown), Dan Geiger	3
11	Likelihood computations using value abstraction 2000 ·Uncertainty in Artificial Intelligence ·Nir Friedman, Dan Geiger, (unknown)	12
12	On the geometry of DAG models with hidden variables. 1999 ·International Conference on Artificial Intelligence and Statistics ·Dan Geiger, David Heckerman, (unknown), Christopher Meek	3
13	A characterization of the bivariate wishart distribution 1998 ·Dan Geiger, David Heckerman	7
14	A practical algorithm for finding optimal triangulations 1997 ·National Conference on Artificial Intelligence ·(unknown), Dan Geiger	39
15	Knowledge representation and inference in similarity networks and Bayesian multinets 1996 ·Artificial Intelligence ·Dan Geiger, David Heckerman	136
16	Learning Bayesian Networks: The Combination of Knowledge and Statistical Data breakdown → 1995 ·Machine Learning ·David Heckerman, Dan Geiger, David M. Chickering	2029
17	Approximation algorithms for the vertex feedback set problem with applications to constraint satisfaction and Bayesian inference 1994 ·Symposium on Discrete Algorithms ·Reuven Bar-Yehuda, Dan Geiger, Joseph Naor, Ron M. Roth	29
18	Learning simple causal structures 1993 ·International Journal of Intelligent Systems ·Dan Geiger, Azaria Paz, Judea Pearl	21
19	BDDMAP: a technology mapper based on a new covering algorithm 1992 ·Design Automation Conference ·David S. Kung, Robert Damiano, (unknown), Dan Geiger	15
20	Conditional independence and its representations 1990 ·Kybernetika ·J. Pearl, Dan Geiger, (unknown)	28

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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