Continuous Graphical Models for Static and Dynamic Distributions: Application to Structural Biology

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Summary

This thesis develops new and improved continuous graphical models, to be used in modeling of protein structure, and develops consistent and efficient algorithms for sparse structure learning and parameter estimation, and inference.

Type
article
Published
2013-01-01
Cited by
2
References
104
Access
Open access

Keywords

Graphical model, Computer science, Inference, Machine learning, Artificial intelligence

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