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Computer Science

D-Index
66
Citations
16960
World Ranking
2334
National Ranking
1165

Overview

Christopher A. Meek is affiliated with Microsoft in the United States and works primarily in the field of Computer Science. Their research spans multiple subfields including Artificial Intelligence, Building and Construction, Environmental Engineering, General Health Professions, and Philosophy.

The scientist's work covers topics such as Building Energy and Comfort Optimization, Environmental Impact and Sustainability, Topic Modeling, Sustainable Building Design and Assessment, Hermeneutics and Narrative Identity, Aging, Elder Care, and Social Issues, as well as Health, Medicine and Society.

Christopher A. Meek has authored several recent publications, including:

  • Graphical Models: Selecting causal and statistical models (2023, OPAL (Open@LaTrobe) (La Trobe University))
  • Synchromesh: Reliable code generation from pre-trained language models (2022, arXiv (Cornell University))
  • On the tradeoffs between embodied and operational carbon in building envelope design: The impact of local climates and energy grids (2022, Energy and Buildings)
  • Learning Math Reasoning from Self-Sampled Correct and Partially-Correct Solutions (2022, arXiv (Cornell University))
  • Spider Realistic Dataset In Structure-Grounded Pretraining for Text-to-SQL (2021, Zenodo (CERN European Organization for Nuclear Research))

The frequent coauthors collaborating with Christopher A. Meek include:

  • Tomás Méndez Echenagucia
  • Teresa Moroseos
  • Oleksandr Polozov
  • C. E. Meek
  • Gabriel Poesia

Their publications commonly appear in the following venues:

  • Energy and Buildings
  • arXiv (Cornell University)
  • OPAL (Open@LaTrobe) (La Trobe University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • SSRN Electronic Journal

Best Publications

  • WikiQA: A Challenge Dataset for Open-Domain Question Answering

    Yi Yang;Wen-tau Yih;Christopher Meek

  • Large-Sample Learning of Bayesian Networks is NP-Hard

    David Maxwell Chickering;David Heckerman;Christopher Meek

  • Systems and methods for allocating placement of content items on a rendered page based upon bid value

    David Chickering;Christopher Meek;David Heckerman;Brian Burdick

  • A Bayesian approach to learning Bayesian networks with local structure

    David Maxwell Chickering;David Heckerman;Christopher Meek

  • Apparatus and accompanying methods for visualizing clusters of data and hierarchical cluster classifications

    David E. Heckerman;Paul S. Bradley;David M. Chickering;Christopher A. Meek

  • Semantic Parsing for Single-Relation Question Answering

    Wen-tau Yih;Xiaodong He;Christopher Meek

  • Visualization of navigation patterns on a Web site using model-based clustering

    Igor Cadez;David Heckerman;Christopher Meek;Padhraic Smyth

  • Similarity measures for short segments of text

    Donald Metzler;Susan Dumais;Christopher Meek

  • The Value of Semantic Parse Labeling for Knowledge Base Question Answering

    Wen-tau Yih;Matthew Richardson;Christopher Meek;Ming-Wei Chang

  • Identifying similarities, periodicities and bursts for online search queries

    Michail Vlachos;Christopher Meek;Zografoula Vagena;Dimitrios Gunopulos

  • Model-Based Clustering and Visualization of Navigation Patterns on a Web Site

    Igor Cadez;David Heckerman;Christopher Meek;Padhraic Smyth

  • A Bayesian Approach to Causal Discovery

    David Heckerman;Christopher Meek;Gregory Cooper

  • Content-targeted advertising for interactive computer-based applications

    Joshua Goodman;Christopher Meek;Carl Kadie

  • The TETRAD project: Constraint based aids to causal model specification.

    Richard Scheines;Peter Spirtes;Clark Glymour;Christopher Meek

  • Dynamic controlling of attribute-specific list for improved object organization

    Christopher A. Meek

  • On the toric algebra of graphical models

    Dan Geiger;Christopher Meek;Bernd Sturmfels

  • Desktop search from mobile device

    Raymond E. Ozzie;Eric J. Horvitz;William H. Gates;Joshua T. Goodman

  • Typed Tensor Decomposition of Knowledge Bases for Relation Extraction

    Kai-Wei Chang;Wen-tau Yih;Bishan Yang;Christopher Meek

  • Systems, methods, computer-readable media and devices for client-based web crawling

    Meek Christopher A;Brill Eric D

  • Visual and multi-dimensional search

    Stephen Lawler;Eric J. Horvitz;Joshua T. Goodman;Anoop Gupta

  • Large-sample learning of bayesian networks is NP-hard

    David Maxwell Chickering;Christopher Meek;David Heckerman

Frequent Co-Authors

David Maxwell Chickering
David Maxwell Chickering Microsoft (United States)
David Heckerman
David Heckerman Microsoft (United States)
Gary W. Flake
Gary W. Flake Independent Scientist / Consultant, US
Dan Geiger
Dan Geiger Technion – Israel Institute of Technology
Eric Horvitz
Eric Horvitz Microsoft (United States)
Joshua T. Goodman
Joshua T. Goodman Microsoft (United States)
Kamal Jain
Kamal Jain Microsoft (United States)
Robert L. Rounthwaite
Robert L. Rounthwaite Microsoft (United States)
Ying Li
Ying Li Microsoft (United States)

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