Summary statistics and approximate bayesian computation are comparable to convolutional neural networks for inferring times to fixation.

Roberts MD, Josephs EB

DOI: 10.64898/2026.02.17.706432
Published: 2026 Feb 18
Container: bioRxiv : the preprint server for biology
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.64898/2026.02.17.706432,
  title = {Summary statistics and approximate bayesian computation are comparable to convolutional neural networks for inferring times to fixation.},
  author = {Roberts MD and Josephs EB},
  year = {2026},
  journal = {bioRxiv : the preprint server for biology},
  doi = {10.64898/2026.02.17.706432},
  url = {https://doi.org/10.64898/2026.02.17.706432}
}

RIS

TY  - JOUR
TI  - Summary statistics and approximate bayesian computation are comparable to convolutional neural networks for inferring times to fixation.
AU  - Roberts MD
AU  - Josephs EB
PY  - 2026
JO  - bioRxiv : the preprint server for biology
DO  - 10.64898/2026.02.17.706432
UR  - https://doi.org/10.64898/2026.02.17.706432
ER  -

APA

MD, R., & EB, J. (2026). Summary statistics and approximate bayesian computation are comparable to convolutional neural networks for inferring times to fixation.. bioRxiv : the preprint server for biology. https://doi.org/10.64898/2026.02.17.706432

Source records

pubmed · retrieved 2026-09-25T10:38:04.222Z