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Fredrik Ronquist

Researcher at Swedish Museum of Natural History

Publications -  128
Citations -  84851

Fredrik Ronquist is an academic researcher from Swedish Museum of Natural History. The author has contributed to research in topics: Monophyly & Markov chain Monte Carlo. The author has an hindex of 54, co-authored 122 publications receiving 76188 citations. Previous affiliations of Fredrik Ronquist include Uppsala University & Florida State University.

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A Fully Web-illustrated Morphological Phylogenetic Study of Relationships among Oak Gall wasps and their Closest Relatives (Hymenoptera: Cynipidae)

TL;DR: The results suggest that WRG are conservative in their host plant preferences but there is no evidence for parallel insect-plant cladogenesis and distributional patterns suggest a possible origin for the oak gall wasps in the Nearctic but the picture is otherwise complicated.
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Bayesian Tests of Topology Hypotheses with an Example from Diving Beetles

TL;DR: Bayesian approaches to model testing in general and to the assessment of topological hypotheses in particular are reviewed, and refined Bayes factor tests show that there is strong support for Suphrodytes nesting inside Hydroporus, and the genera are therefore synonymized.
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Probabilistic Graphical Model Representation in Phylogenetics

TL;DR: An introduction to graphical models for phylogeneticists and extend the standard graphical model representation to the realm of phylogenetics is provided and a new graphical model component, tree plates, is introduced to capture the changing structure of the subgraph corresponding to a phylogenetic tree.
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Automated Taxonomic Identification of Insects with Expert-Level Accuracy Using Effective Feature Transfer from Convolutional Networks

TL;DR: An effective method of CNN feature transfer is developed, which achieves expert-level accuracy in taxonomic identification of insects with training sets of 100 images or less per category, depending on the nature of data set.
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Closing the gap between rocks and clocks using total-evidence dating.

TL;DR: DRA in the mammalian dataset can be addressed by introducing a modest extra penalty for ghost lineages that are unobserved in the fossil record, for instance by assuming rapid diversification, rare extinction or high fossil sampling rate; any of these assumptions produces highly congruent divergence time estimates with a minimal gap between rocks and clocks.