Constraint-based Sampling

Constraint-Based Sampling is a conformational sampling method that restricts the exploration of molecular configurations to satisfy predefined geometric or physical constraints, thereby reducing the search space by eliminating degrees of freedom incompatible with those constraints.

29

Publications

1.7K

Citations

93

Authors

49

Institutions

Publications per year

2017–2026

10

Authors

93

  1. AW
    Andrew Witkin

    Carnegie Mellon University, United States

    2 publications · 562 citations

    2

    h-index

  2. AM
    Alan Malek

    Queensland University of Technology, Australia

    2 publications · 41 citations

    2

    h-index

  3. PL
    Peter L. Bartlett

    University of California, Berkeley, United States

    2 publications · 41 citations

    2

    h-index

  4. PS
    Paul S. Heckbert

    Carnegie Mellon University, United States

    2 publications · 562 citations

    2

    h-index

  5. YA
    Yasin Abbasi-Yadkori

    University of Alberta, Canada

    2 publications · 41 citations

    2

    h-index

1–5 of 93

Venues

  1. Bioinformatics

    2 publications · 121 citations

    2

    h-index

  2. Journal of Computer-Aided Molecular Design

    2 publications · 39 citations

    2

    h-index

  3. arXiv (Cornell University)

    Repository · 1 publications · 30 citations

    1

    h-index

  4. Mathematical Programming

    1 publications · 42 citations

    1

    h-index

  5. Journal of Statistical Physics

    1 publications · 28 citations

    1

    h-index

1–5