Peer-reviewedLicence not statedGenetics
Likelihood-Free Inference in High-Dimensional Models
Related
- High-Dimensional Two-Sample Inference via Marginal Likelihood-Ratio Rank Statistics
- SLICE: Sequential Likelihood-Free Inference via Conformal E-Values
- Likelihood-free inference with nuisance parameters through normalizing flows
- Likelihood-Free Schrödinger--Föllmer Sampling for Bayesian Inference with Fixed-Proposal Reuse
- Honest Inference for High-Dimensional Linear Models
BibTeX
@article{kousathanas2026likelihoodfree,
title = {{Likelihood-Free Inference in High-Dimensional Models}},
author = {Athanasios Kousathanas and Christoph Leuenberger and Jonas Helfer and Mathieu Quinodoz and Matthieu Foll and Daniel Wegmann},
journal = {Genetics},
year = {2026},
month = oct,
doi = {10.1534/genetics.116.187567},
url = {https://hal.science/hal-05842800v1},
}
RIS
TY - JOUR
TI - Likelihood-Free Inference in High-Dimensional Models
AU - Athanasios Kousathanas
AU - Christoph Leuenberger
AU - Jonas Helfer
AU - Mathieu Quinodoz
AU - Matthieu Foll
AU - Daniel Wegmann
PY - 2026
DA - 2026/10/28
JO - Genetics
DO - 10.1534/genetics.116.187567
UR - https://hal.science/hal-05842800v1
SN - 1943-2631
ER -