Brian Milch

1.8k citations
20 papers · 1.2k · h-index 13

Impact in

Papers in

Brian Milch

20 papers receiving 1.1k citations

Peers

Brian Milch
Comparison fields: 5 of 75
  • Management Science and Operations Research 342
  • Artificial Intelligence 903
  • Signal Processing 160
  • Information Systems 269
  • Computer Networks and Communications 178
Replace Pável Calado with:
Pável Calado Portugal
Mi Zhang China
Josiane Mothe France
Marco Schaerf Italy
Jianguo Lü Canada
Paolo Viappiani France
Francesco Guerra Italy
Saravanan Thirumuruganathan United States
Xuehua Shen United States
John R. Goodall United States
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Citations per field
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Citations per year

Countries citing papers authored by Brian Milch

Since Specialization
Citations

This map shows the geographic impact of Brian Milch'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 Brian Milch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Brian Milch more than expected).

Fields of papers citing papers by Brian Milch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Brian Milch. 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 Brian Milch. The network helps show where Brian Milch may publish in the future.

Co-authors

The 25 scholars most cited alongside Brian Milch, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Brian Milch Line = papers co-authored together Brian Milch links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 2003270
2
Identity Uncertainty and Citation Matching
2002222
3 2007222
4 2003127
5
Lifted probabilistic inference with counting formulas
2008125
6
Probabilistic models with unknown objects
200634
7 200732
8 200232
9
Approximate inference for infinite contingent Bayesian networks
200530
10 200530
11
First-Order Probabilistic Models for Information Extraction
200319
12
Multi-Agent Filtering with Infinitely Nested Beliefs
200816
13 201315
14
Ignorable Information in Multi-Agent Scenarios
20086
15 20035
16
Random-World Semantics and Syntactic Independence for Expressive Languages
20084
17
Structured models for multi-agent interactions
20012
18
Reasoning about Large Populations with Lifted Probabilistic Inference
20072
19 20082
20
Artificial General Intelligence through Large-Scale, Multimodal Bayesian Learning
20081

About Brian Milch

Brian Milch is a scholar working on Artificial Intelligence, Management Science and Operations Research, Computer Networks and Communications, Information Systems and Computer Vision and Pattern Recognition, having authored 20 papers that have together received 1.2k indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (13 papers), Data Quality and Management (7 papers), Web Data Mining and Analysis (3 papers), Game Theory and Applications (3 papers), Advanced Database Systems and Queries (3 papers), Advanced Text Analysis Techniques (3 papers), Logic, Reasoning, and Knowledge (3 papers) and Topic Modeling (3 papers). The work is most often cited by research in Management Science and Operations Research (342 citations), Artificial Intelligence (903 citations), Signal Processing (160 citations), Information Systems (269 citations) and Computer Networks and Communications (178 citations). Brian Milch has collaborated with scholars based in United States, Germany and Spain. Frequent co-authors include Daphne Koller, Stuart Russell, Bhaskara Marthi, Ilya Shpitser, Hanna Pasula, Andrey Kolobov, David Sontag, Monika Henzinger, Bay-Wei Chang and Sergey Brin. Their work appears in journals such as IEEE Intelligent Systems, World Wide Web, Games and Economic Behavior, Lecture notes in computer science and International Conference on Artificial Intelligence and Statistics.

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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