• Mendoza, I.*, Torchylo A.*, Sainrat T., et al., “The Blending ToolKit: A simulation framework for evaluation of galaxy detection and deblending”. arXiv preprint arXiv:2409.06986. Submitted to OJA.

  • Mendoza, I., Mansfield, P., Wang, K., Avestruz, C., “MultiCAM: A multivariable framework for connecting the mass accretion history of haloes with their properties”. Monthly Notices of the Royal Astronomical Society, Volume 523, Issue 4, August 2023, Pages 6386–6400, https://doi.org/10.1093/mnras/stad1768.

  • Mendoza, I., Liu, R., Hansen, D., Zhao, Z., Pang, Z., Avestruz, C., Regier, J., and LSST Dark Energy Collaboration, “Simulation-Based Inference for Probabilistic Light Source Detection, Deblending, and Measurement”. Submitted to the Dark Energy Science Collaboration (DESC) for internal review.

  • Wang M.*, Mendoza I.*, Wang C., Avestruz C., Regier J., “Statistical Inference for Coadded Astronomical Images”. arXiv:2211.09300. Accepted to the Machine Learning and the Physical Sciences Workshop at the 36th conference on Neural Information Processing Systems (NeurIPS).

  • Hansen, D.*, Mendoza, I.*, Liu, R., Pang, Z., Zhao, Z., Avestruz, C., and Regier, J., “Scalable Bayesian Inference for Detection and Deblending in Astronomical Images”. arXiv:2207.05642. Accepted to the ICML 2022 Workshop on Machine Learning for Astrophysics.

  • Sanchez, J., Mendoza, I., Kirkby, D. P., Burchat, P. R., for the LSST Dark Energy Science Collaboration, “Effects of overlapping sources on cosmic shear estimation: Statistical sensitivity and pixel-noise bias”. Journal of Cosmology and Astroparticle Physics, vol. 2021, no. 7, 2021. https://doi.org/10.1088/1475-7516/2021/07/043.

Note: Asterisks denote equal contribution.

External list of publications

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