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pmwd: A Differentiable Cosmological Particle-Mesh $N$-body Library

 Yin Li , Libin Lu , Chirag Modi , Drew Jamieson , Yucheng Zhang , et al.
2022
Pré-publication, Document de travail hal-03892304v1

An information-based metric for observing strategy optimization, demonstrated in the context of photometric redshifts with applications to cosmology

 Alex I. Malz , Francois Lanusse , John Franklin Crenshaw , Melissa L. Graham
2021
Pré-publication, Document de travail hal-03217524v1
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3D galaxy clustering with future wide-field surveys: Advantages of a spherical Fourier-Bessel analysis

 F. Lanusse , A. Rassat , J.-L. Starck
Astronomy and Astrophysics - A&A, 2015, 578, pp.A10. ⟨10.1051/0004-6361/201424456⟩
Article dans une revue cea-01300572v1

The LSST-DESC 3x2pt Tomography Optimization Challenge

 Joe Zuntz , François Lanusse , Alex I. Malz , Angus H. Wright , Anže Slosar , et al.
Open J.Astrophys., 2021, 4, pp.13418. ⟨10.21105/astro.2108.13418⟩
Article dans une revue hal-03346545v1
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ShapeNet: Shape constraint for galaxy image deconvolution

 F. Nammour , U. Akhaury , J. N. Girard , F. Lanusse , F. Sureau , et al.
Astronomy and Astrophysics - A&A, 2022, 663, pp.A69. ⟨10.1051/0004-6361/202142626⟩
Article dans une revue cea-03728008v1
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Differentiable Stochastic Halo Occupation Distribution

 Benjamin Horowitz , Changhoon Hahn , Francois Lanusse , Chirag Modi , Simone Ferraro
Mon.Not.Roy.Astron.Soc., 2024, 529 (3), pp.2473-2482. ⟨10.1093/mnras/stae350⟩
Article dans une revue hal-03866311v1
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A deep learning approach to test the small-scale galaxy morphology and its relationship with star formation activity in hydrodynamical simulations

 Lorenzo Zanisi , Marc Huertas-Company , François Lanusse , Connor Bottrell , Annalisa Pillepich , et al.
Monthly Notices of the Royal Astronomical Society, 2021, 501 (3), pp.4359-4382. ⟨10.1093/mnras/staa3864⟩
Article dans une revue hal-03451411v1
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Likelihood-free inference with neural compression of DES SV weak lensing map statistics

 Niall Jeffrey , Justin Alsing , François Lanusse
Monthly Notices of the Royal Astronomical Society, 2021, 501 (1), pp.954-969. ⟨10.1093/mnras/staa3594⟩
Article dans une revue hal-02959520v1

Validating Synthetic Galaxy Catalogs for Dark Energy Science in the LSST Era

 Eve Kovacs , Yao-Yuan Mao , Michel Aguena , Anita Bahmanyar , Adam Broussard , et al.
Open J.Astrophys., 2022, 5, pp.astro.2110.03769. ⟨10.21105/astro.2110.03769⟩
Article dans une revue hal-03401568v1

Adaptive wavelet distillation from neural networks through interpretations

 Wooseok Ha , Chandan Singh , Francois Lanusse , Srigokul Upadhyayula , Bin Yu
2021
Pré-publication, Document de travail hal-03451718v1

Improving Weak Lensing Mass Map Reconstructions using Gaussian and Sparsity Priors: Application to DES SV

 N. Jeffrey , F.B. Abdalla , O. Lahav , F. Lanusse , J.-L. Starck , et al.
Mon.Not.Roy.Astron.Soc., 2018, 479 (3), pp.2871-2888. ⟨10.1093/mnras/sty1252⟩
Article dans une revue hal-01707543v1
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Sparse reconstruction of the dark matter mass map from weak gravitational lensing

 Francois Lanusse
Cosmology and Extra-Galactic Astrophysics [astro-ph.CO]. Université Paris Saclay (COmUE), 2015. English. ⟨NNT : 2015SACLS102⟩
Thèse tel-01281927v1
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Deep generative models for galaxy image simulations

 François Lanusse , Rachel Mandelbaum , Siamak Ravanbakhsh , Chun-Liang Li , Peter Freeman , et al.
Monthly Notices of the Royal Astronomical Society, 2021, 504 (4), pp.5543-5555. ⟨10.1093/mnras/stab1214⟩
Article dans une revue hal-03451832v1
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Denoising Score-Matching for Uncertainty Quantification in Inverse Problems

 Zaccharie Ramzi , Benjamin Rémy , Francois Lanusse , Jean-Luc Starck , Philippe Ciuciu
NeurIPS 2020 - 34th Conference on Neural Information Processing Systems / Workshop on Deep Learning and Inverse Problems, Dec 2020, Vancouver / Virtuel, Canada
Communication dans un congrès hal-03020167v1

The LSST DESC DC2 Simulated Sky Survey

 Bela Abolfathi , David Alonso , Robert Armstrong , Éric Aubourg , Humna Awan , et al.
Astrophys.J.Suppl., 2021, 253 (1), pp.31. ⟨10.3847/1538-4365/abd62c⟩
Article dans une revue hal-02981230v1

Core Cosmology Library: Precision Cosmological Predictions for LSST

 Nora Elisa Chisari , David Alonso , Elisabeth Krause , C. Danielle Leonard , Philip Bull , et al.
Astrophys.J.Suppl., 2019, 242 (1), pp.2. ⟨10.3847/1538-4365/ab1658⟩
Article dans une revue hal-01982819v1

Modeling halo and central galaxy orientations on the SO(3) manifold with score-based generative models

 Yesukhei Jagvaral , Rachel Mandelbaum , Francois Lanusse
36th Conference on Neural Information Processing Systems, Nov 2022, New Orleans, United States
Communication dans un congrès hal-03921105v1
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Galaxies and haloes on graph neural networks: Deep generative modelling scalar and vector quantities for intrinsic alignment

 Yesukhei Jagvaral , François Lanusse , Sukhdeep Singh , Rachel Mandelbaum , Siamak Ravanbakhsh , et al.
Monthly Notices of the Royal Astronomical Society, 2022, 516 (2), pp.2406-2419. ⟨10.1093/mnras/stac2083⟩
Article dans une revue hal-04310975v1

FlowPM: Distributed TensorFlow implementation of the FastPM cosmological N-body solver

 Chirag Modi , Francois Lanusse , Uros Seljak
Astron.Comput., 2021, 37, pp.100505. ⟨10.1016/j.ascom.2021.100505⟩
Article dans une revue hal-02999554v1

Sparse reconstruction of the merging A520 cluster system

 Austin Peel , François Lanusse , Jean-Luc Starck
Astrophys.J., 2017, 847 (1), pp.23. ⟨10.3847/1538-4357/aa850d⟩
Article dans une revue hal-01645857v1

Deep learning dark matter map reconstructions from DES SV weak lensing data

 Niall Jeffrey , François Lanusse , Ofer Lahav , Jean-Luc Starck
Monthly Notices of the Royal Astronomical Society, 2020, 492 (4), pp.5023-5029. ⟨10.1093/mnras/staa127⟩
Article dans une revue hal-02290809v1
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Dark Energy Survey Year 3 results: curved-sky weak lensing mass map reconstruction

 N. Jeffrey , M. Gatti , C. Chang , L. Whiteway , U. Demirbozan , et al.
Monthly Notices of the Royal Astronomical Society, 2021, 505, pp.4626-4645. ⟨10.1093/mnras/stab1495⟩
Article dans une revue hal-03261539v1
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The DAWES review 10: The impact of deep learning for the analysis of galaxy surveys

 Marc Huertas-Company , François Lanusse
Publications of the Astronomical Society of Australia, 2023, 40, pp.e001. ⟨10.1017/pasa.2022.55⟩
Article dans une revue hal-03822825v1

JAX-COSMO: An End-to-End Differentiable and GPU Accelerated Cosmology Library

 Jean-Eric Campagne , François Lanusse , Joe Zuntz , Alexandre Boucaud , Santiago Casas , et al.
Open J.Astrophys., 2023, 6, pp.1-15. ⟨10.21105/astro.2302.05163⟩
Article dans une revue hal-04007879v1
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Anomaly detection in Hyper Suprime-Cam galaxy images with generative adversarial networks

 Kate Storey-Fisher , Marc Huertas-Company , Nesar Ramachandra , Francois Lanusse , Alexie Leauthaud , et al.
Monthly Notices of the Royal Astronomical Society, 2021, 508 (2), pp.2946-2963. ⟨10.1093/mnras/stab2589⟩
Article dans une revue hal-03451418v1

Transformation Importance with Applications to Cosmology

 Chandan Singh , Wooseok Ha , Francois Lanusse , Vanessa Boehm , Jia Liu , et al.
2021
Pré-publication, Document de travail hal-03451860v1

CosmicRIM : Reconstructing Early Universe by Combining Differentiable Simulations with Recurrent Inference Machines

 Chirag Modi , François Lanusse , Uroš Seljak , David N. Spergel , Laurence Perreault-Levasseur
2021
Pré-publication, Document de travail hal-03224793v1

Hybrid Physical-Neural ODEs for Fast N-body Simulations

 Denise Lanzieri , François Lanusse , Jean-Luc Starck
39th International Conference on Machine Learning Conference, Jul 2022, Baltimore, United States
Communication dans un congrès hal-03736358v1

Towards solving model bias in cosmic shear forward modeling

 Benjamin Remy , Francois Lanusse , Jean-Luc Starck
36th Conference on Neural Information Processing Systems, Nov 2022, New Orleans, United States
Communication dans un congrès hal-03846589v1

The Role of Machine Learning in the Next Decade of Cosmology

 Michelle Ntampaka , Camille Avestruz , Steven Boada , João Caldeira , Jessi Cisewski-Kehe , et al.
2019
Pré-publication, Document de travail hal-02065883v1
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