Author of the publication

Validation of Approximate Likelihood and Emulator Models for Computationally Intensive Simulations.

, , , , , and . AISTATS, volume 108 of Proceedings of Machine Learning Research, page 3349-3361. PMLR, (2020)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

 

Other publications of authors with the same name

Occlusion models for natural images: A statistical study of a scale-invariant dead leaves model, , and . International Journal of Computer Vision, 41 (1-2): 35--59 (2001)Likelihood-Free Frequentist Inference: Confidence Sets with Correct Conditional Coverage, , , , and . (2021)cite arxiv:2107.03920Comment: 59 pages, 14 figures, code available at https://github.com/Mr8ND/ACORE-LFI.Classification under Nuisance Parameters and Generalized Label Shift in Likelihood-Free Inference., , , , , and . ICML, OpenReview.net, (2024)Toward a Full Probability Model of Edges in Natural Images., and . ECCV (1), volume 2350 of Lecture Notes in Computer Science, page 328-342. Springer, (2002)An Optimal Transportation Approach for Nuclear Structure-Based Pathology., , , , , and . IEEE Trans. Med. Imaging, 30 (3): 621-631 (2011)Simulator-Based Inference with WALDO: Confidence Regions by Leveraging Prediction Algorithms and Posterior Estimators for Inverse Problems., , , , and . AISTATS, volume 206 of Proceedings of Machine Learning Research, page 2960-2974. PMLR, (2023)Treelets | A Tool for Dimensionality Reduction and Multi-Scale Analysis of Unstructured Data., and . AISTATS, volume 2 of JMLR Proceedings, page 259-266. JMLR.org, (2007)Validation of Approximate Likelihood and Emulator Models for Computationally Intensive Simulations., , , , , and . AISTATS, volume 108 of Proceedings of Machine Learning Research, page 3349-3361. PMLR, (2020)Conditional density estimation tools in python and R with applications to photometric redshifts and likelihood-free cosmological inference., , , , , and . Astron. Comput., (2020)Confidence Sets and Hypothesis Testing in a Likelihood-Free Inference Setting., , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 2323-2334. PMLR, (2020)