International CHASC AstroStatistics Centre

Topics in Astrostatistics

AY 2023-2024

Archive

Schedule	Wednesdays Noon - 1:30pm Eastern Time
Location	SC-706 + Zoom

Presentations
Cecilia Garraffo (CfA) Sep 06 Noon EDT SC-706	AstroAI: Integrating Artificial Intelligence into Astrophysics Abstract: AstroAI, launched at the Center for Astrophysics \| Harvard & Smithsonian (CfA) in November 2022, is a novel initiative focused on developing machine learning (ML) and artificial intelligence (AI) algorithms to further astrophysical research. Its inception was driven by the recognized need, both within the CfA and the broader scientific community, for dependable and interpretable models in astrophysics research. At its core, AstroAI aims to create AI and ML models designed for astrophysical discovery, emphasizing a multidisciplinary approach and collaboration among a diverse group of researchers. This talk will outline the progress and growth of AstroAI since its beginning and highlight some of the key projects undertaken by our team, and showcase a few of our projects and their transformative potential in astrophysical research. Presentation Video [!yt]
Mengyang Gu (UC Santa Barbara) Sep 13 Noon EDT SC-706	Calibration of imperfect geophysical models by multiple satellite interferograms with measurement bias Abstract: Model calibration consists of using experimental or field data to estimate the unknown parameters of a mathematical model. The presence of model discrepancy and measurement bias in the data complicates this task. Satellite interferograms, for instance, are widely used for calibrating geophysical models in geological hazard quantification. In this work, we used satellite interferograms to relate ground deformation observations to the properties of the magma chamber at Kilauea Volcano in Hawai`i. We derived closed-form marginal likelihoods and implemented posterior sampling procedures that simultaneously estimate the model discrepancy of physical models, and the measurement bias from the atmospheric error in satellite interferograms. We found that model calibration by aggregating multiple interferograms and downsampling the pixels in the interferograms can reduce the computation complexity compared to calibration approaches based on multiple data sets. The conditions that lead to no loss of information from data aggregation and downsampling are studied. Simulation illustrates that both discrepancy and measurement bias can be estimated, and real applications demonstrate that modeling both effects helps obtain a reliable estimation of a physical model's unobserved parameters and enhance its predictive accuracy. We implement the computational tools in the RobustCalibration package available on CRAN. References: Gu, M., & Wang, L. (2018). Scaled Gaussian stochastic process for computer model calibration and prediction. SIAM/ASA Journal on Uncertainty Quantification, 6(4), 1555-1583 Gu, M., Xie, F., & Wang, L. (2022). A Theoretical Framework of the Scaled Gaussian Stochastic Process in Prediction and Calibration. SIAM/ASA Journal on Uncertainty Quantification, 10(4), 1435-1460. Gu, M., Anderson, K., & McPhillips, E. (2023). Calibration of imperfect geophysical models by multiple satellite interferograms with measurement bias. Technometrics, in press, arxiv:1810.11664 [!arXiv] Gu, M., He, Y., Liu, X., & Luo Y. (2023). Ab initio uncertainty quantification in scattering analysis of microscopy arXiv:2309.02468 [!arXiv] Presentation slides [.pdf] Presentation video [!yt]
Aneta Siemiginowska (CfA) Oct 11, 2023 Noon EDT SC-706	TBC: on Time delays
Pavlos Protopapas (SEAS) Oct 18, 2023 Noon EDT SC-706	TBC: Residual-based_error_bound_for_physics-informed_neural_networks_ML Reference: Liu et al. 2023, arXiv:2306.03786 [!arXiv]
Xiangyu Zhang (Minnesota) Feb 21, 2024 11am CST Zoom	Smooth tests for line emission detection under high background in high-resolution X-ray spectra

Archive
Fall/Winter 2004-2005 Siemiginowska, A. / Connors, A. / Kashyap, V. / Zezas, A. / Devor, J. / Drake, J. / Kolaczyk, E. / Izem, R. / Kang, H. / Yu, Y. / van Dyk, D.
Fall/Winter 2005-2006 van Dyk, D. / Ratner, M. / Jin, J. / Park, T. / CCW / Zezas, A. / Hong, J. / Siemiginowska, A. & Kashyap, V. / Meng, X.-L.
Fall/Winter 2006-2007 Lee, H. / Connors, A. / Protopapas, P. / McDowell, J., / Izem, R. / Blondin, S. / Lee, H. / Zezas, A., & Lee, H. / Liu, J.C. / van Dyk, D. / Rice, J.
Fall/Winter 2007-2008 Connors, A., & Protopapas, P. / Steiner, J. / Baines, P. / Zezas, A. / Aldcroft, T.
Fall/Winter 2008-2009 H. Lee / A. Connors, B. Kelly, & P. Protopapas / P. Baines / A. Blocker / J. Hong / H. Chernoff / Z. Li / L. Zhu (Feb) / A. Connors (Pt.1) / A. Connors (Pt.2) / L. Zhu (Mar) / E. Kolaczyk / V. Liublinska / N. Stein
Fall/Winter 2009-2010 A.Connors / B.Kelly / N.Stein, P.Baines / D.Stenning / J. Xu / A.Blocker / P.Baines, Y.Yu / V.Liublinska, J.Xu, J.Liu / Meng X.L., et al. / A. Blocker, et al. / A. Siemiginowska / D. Richard / A. Blocker / Xie X. / Xu J. / V. Liublinska / L. Jing
AcadYr 2010-2011 Astrostat Haiku / P. Protopapas / A. Zezas & V. Kashyap / A. Siemiginowska / K. Mandel / N. Stein / A. Mahabal / Hong J.S. / D. Stenning / A. Diaferio / Xu J. / B. Kelly / P. Baines & I. Udaltsova / M. Weber
AcadYr 2011-2012 A. Blocker / Astro for Stat / B. Kelly / R. D'Abrusco / E. Turner / Xu J. / T. Loredo / A. Blocker / P. Baines / A. Zezas et al. / Min S. & Xu J. / O. Papaspiliopoulos / Wang L. / T. Laskar
AcadYr 2012-2013 N. Stein / A. Siemiginowska / D. Cervone / R. Dawson / P. Protopapas / K. Reeves / Xu J. / J. Scargle / Min S. / Wang L. & D. Jones / J. Steiner / B. Kelly / K. McKeough
AcadYr 2013-2014 Meng X.-L. / Meng X.-L., K. Mandel / A. Siemiginowska / S. Vrtilek & L. Bornn / Lazhi W. / D. Jones / R. Wong / Xu J. / van Dyk D. / Feigelson E. / Gopalan G. / Min S. / Smith R. / Zezas A. / van Dyk D. / Hyungsuk T. / Czerny, B. / Jones D. / Liu K. / Zezas A.
AcadYr 2014-2015 Vegetabile, B. & Aldcroft, T., / H. Jae Sub / Siemiginowska, A. & Kashyap, V. / Pankratius, V. / Tak, H. / Brenneman, L. / Johnson, J. / Lynch, R.C. / Fan, M.J. / Meng, X.-L. / Gopalan, G. / Jiao, X. / Si, S. / Udaltsova, I. & Zezas, A. / Wang, L. / Tak, H. / Eadie, G. / Czekala, I. / Stenning, D. / Stampoulis, V. / Aitkin, M. / Algeri, S. / Barnacka, A.
AcadYr 2015-2016 DePasquale, J. / Tak, H. / Meng, X.-L. / Jones, D. / Huang, J. / Blanchard, P. / Chen, Y. & Wang, X. / Tak, H. / Mandel, K. / Jiao, X. / Wang, X. & Chen, Y. / IACHEC WG / Si, S. / Drake, J. / Stampoulis, V. / Algeri, S. / Stein, N. / Chunzhe, Z. / Andrews, J. / Vrtilek, S. / Udaltsova, I. & Stampoulis, V.
AcadYr 2016-2017 Wang, X. & Chen, Y. / Kashyap, V., Siemiginowska, A., & Zezas, A. / Stampoulis, V. / Portillo, S. / Zhang, K. / Mandel, K. / DiStefano, R. / Finkbeiner, D. & Meade, B. / Gong, R. / Shihao Y. / Zhirui, H. / Xufei, W. / Campos, L. / Tak, H. / Xufei, W. / Jones, D. / Algeri, S. / Speagle, J. / Czekala, I.
AcadYr 2017-2018 AstroStat Day / Speagle, J. / Collin, G. / McKeough, K. & Yang, S. / McKeough, K. & Campos, L. / M. Ntampaka / H. Marshall / D. Huppenkothen / X. Yu / R. DiStefano / J. Yee / H. Tak / A. Avelino
AcadYr 2018-2019 Stenning, D. / Dvorkin, C. / Sottosanti, A. / Yu, X. / Chen, Y. / Jones, D. / Lee, T.C.-M. / Tak, H. / Kashyap, V., McKeough, K., Campos, L., et al. / Baines, P. / Collin, G. / Muthukrishna, D. / Zhang, D. / Algeri, S. / Janson, L. / Ward, S. / de Beurs, Z.
AcadYr 2019-2020 McKeough, K. / Astudillo, J. & Protopapas, P. / Zezas, A. / Speagle, J. / Meng, X.-L., Siemiginowska, A., & Kashyap, V. / Bonfini, P. / Liu, C. / Guenther, H. / Castrillon, J. / McKeough, K. / Broekgaarden, F. / Autenrieth, M. / Motta, G. / Zucker, C. / Tak, H. / Kashyap, V. & Wang, X. / Wang, J. / Wang, X. & Ingram, J.
AcadYr 2020-2021 Diaz Rivero, A. / Marshall, H. & Chen, Y. / McKeough, K. / Chen, Y. / Patil, A. / Jerius, D. / Wang, X. / Siemiginowska, A. / Xu, C. / Picquenot, A. / Jacovich, T. / Geringer-Sameth, A. / Toulis, P. / Donath, A. / Ergin, T. / Phillipson, R. / Sun, H. / Autenrieth, M.
AcadYr 2021-2022 Makinen, T.L. / Siemiginowska, A. / Fox-Fortino, W. / Reddy, K. / Primini, F. / Mishra-Sharma, S. / Meyer, A. / Janson, L. / Group
AcadYr 2022-2023 Saydjari, A. / Rau, M.M. / McKimm, H. / Sairam, L. / Meyer, A. / SCMA8 / Kochanski, N. & Chen, Y. / Jones, G. / ISI WSC / Li, D.D.
AcadYr 2023-2024 Garraffo, C. / Gu, M. / Siemiginowska, A. / Protopapas, P. / Zhang, X.

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