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Inferring subhalo effective density slopes from strong lensing observations with neural likelihood-ratio estimation


Aug 29, 2022
Gemma Zhang, Siddharth Mishra-Sharma, Cora Dvorkin

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* 11 pages, 5 figures 

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Uncovering dark matter density profiles in dwarf galaxies with graph neural networks


Aug 26, 2022
Tri Nguyen, Siddharth Mishra-Sharma, Reuel Williams, Lina Necib

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* 9 + 11 pages, 4 + 9 figures 

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Strong Lensing Source Reconstruction Using Continuous Neural Fields


Jun 29, 2022
Siddharth Mishra-Sharma, Ge Yang

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* 8+2 pages, 3+2 figures, accepted at the Machine Learning for Astrophysics Workshop at ICML 2022 

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Machine Learning and Cosmology


Mar 15, 2022
Cora Dvorkin, Siddharth Mishra-Sharma, Brian Nord, V. Ashley Villar, Camille Avestruz, Keith Bechtol, Aleksandra Ćiprijanović, Andrew J. Connolly, Lehman H. Garrison, Gautham Narayan, Francisco Villaescusa-Navarro

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* Contribution to Snowmass 2021. 32 pages 

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A neural simulation-based inference approach for characterizing the Galactic Center $γ$-ray excess


Oct 13, 2021
Siddharth Mishra-Sharma, Kyle Cranmer

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* 20+3 pages, 10+4 figures 

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Inferring dark matter substructure with astrometric lensing beyond the power spectrum


Oct 04, 2021
Siddharth Mishra-Sharma

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* 10 pages, 3 figures, extended version of paper submitted to the Machine Learning and the Physical Sciences workshop at NeurIPS 2021 

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Semi-parametric $γ$-ray modeling with Gaussian processes and variational inference


Oct 20, 2020
Siddharth Mishra-Sharma, Kyle Cranmer

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* 8 pages, 1 figure, extended abstract submitted to the Machine Learning and the Physical Sciences Workshop at NeurIPS 2020 

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Mining for Dark Matter Substructure: Inferring subhalo population properties from strong lenses with machine learning


Oct 17, 2019
Johann Brehmer, Siddharth Mishra-Sharma, Joeri Hermans, Gilles Louppe, Kyle Cranmer

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* 23 pages, 6 figures, code available at https://github.com/smsharma/mining-for-substructure-lens; v2, minor changes to text, version accepted in ApJ 

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