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Learn the Universe -- an ML X Cosmology Workshop

Aug 24 – 27, 2021
Flatiron Institute
America/New_York timezone

Contribution List

35 out of 35 displayed
  1. 2. Introduction- Welcome & Outline of the workshop
    8/24/21, 10:00 AM
  2. 7. Roger de Belsunce: Unbiased inference from large-scale CMB data using likelihood-approximation schemes
    8/24/21, 10:15 AM

    REMOTE

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  3. 8. ChangHoon Hahn: Higher-Order LSS with SBI
    8/24/21, 10:30 AM
  4. 9. Ben Horowitz: hyphy - Conditional Posterior Surrogate Modeling of Hydrodynamical Physics
    8/24/21, 10:45 AM

    REMOTE

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  5. 3. Boryana Hadzhiyska: TBD
    8/24/21, 11:00 AM
  6. 34. Digvijay Wadekar : Symbolic regression for cluster mass estimation
    8/24/21, 11:15 AM
  7. 4. Unstructured Section: Problems we can't solve with current tools that we may have a shot with ML
    8/24/21, 12:15 PM

    Chair: Simone Ferraro & Colin Hill

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  8. 19. Sihao Cheng: The scattering transform in cosmology, or, a CNN without Training
    8/24/21, 2:00 PM
  9. 20. Kate Storey-Fisher: Emulation of Summary Statistics for Cosmology from Galaxy Surveys
    8/24/21, 2:15 PM
  10. 21. Agnès Ferté: Categorizing cosmological models with unsupervised learning
    8/24/21, 2:30 PM
  11. 22. Colin Hill: Non-Gaussian Information in CMB Secondary Anisotropies
    8/24/21, 2:45 PM
  12. 23. Luisa Lucie-Smith: Deep learning insights into dark matter halo formation
    8/24/21, 3:00 PM

    REMOTE

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  13. 6. Unstructured Section: Have non-Gaussian statistics been made redundant?
    8/24/21, 4:15 PM

    Chair: Zoltan Haiman

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  14. 10. Francisco Villaescusa-Navarro: The Cosmology and Astrophysics with Machine Learning Simulations (CAMELS) project
    8/25/21, 10:00 AM
  15. 11. Siamak Ravanbakhsh: deep Networks for Spherical Data
    8/25/21, 10:15 AM
  16. 12. Neerav Kaushal: Mapping from Fast Simulations to Full N-body Simulations
    8/25/21, 10:30 AM
  17. 13. Yin Li: Cosmological Forward Modeling with Adjoint Method
    8/25/21, 10:45 AM
  18. 14. Leander Thiele: DeepSets applied to Clusters: Machine learning the Lagrangian way
    8/25/21, 11:00 AM
  19. 15. Biwei Dai: Translation and Rotation Equivariant Normalizing Flow (TRENF) for Optimal Cosmological Analysis
    8/25/21, 2:00 PM
  20. 16. David Yallup : Principled Bayesian Neural Networks
    8/25/21, 2:15 PM
  21. 17. Miles Cranmer: Histogram Pooling Operators for Interpretable Deep Learning in Cosmology
    8/25/21, 2:30 PM
  22. 18. Anima Anandkumar: AI4 Science A revolution in the making
    8/25/21, 2:45 PM

    REMOTE

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  23. 35. Michael Eickenberg: Wavelet Modulus Integrals for Parameter Estimation
    8/25/21, 3:00 PM
  24. 24. Andrina Nicola : Forecasting cosmological and astrophysical constraints from electron-matter cross-correlations
    8/26/21, 11:30 AM
  25. 25. Christina Kreisch: Precision Cosmology from Voids in the Machine Learning Era
    8/26/21, 11:45 AM
  26. 26. Ira Wolfson: The Fault In Our Spectrum: A 'no go' on small field models analytics
    8/26/21, 12:00 PM
  27. 27. Adrian Bayer: The Look-Elsewhere Effect
    8/26/21, 12:15 PM
  28. 28. Max Lee: Gradient based inference in cosmology using MADLens
    8/26/21, 12:30 PM
  29. 36. Alina Sabyr: Cosmological Constraints from Weak Lensing Peaks: Can Halo Models Accurately Predict Peak Counts?
    8/26/21, 12:45 PM
  30. 30. Anima Anandkumar, “ AI4 Science A revolution in the making “
    8/26/21, 2:00 PM

    REMOTE

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  31. 29. Greg Bryan, Introducing the Simons Collaboration “Learning the Universe”
    8/26/21, 2:15 PM
  32. 33. Rachel Somerville: New methods to model galaxy formation so that we can Learn the Universe
    8/26/21, 2:30 PM
  33. 31. Ana Maria Delgado: Modeling Galaxy-Halo connection with Machine Learning
    8/26/21, 2:45 PM
  34. 32. Sultan Hassan: HIFlow: Fast Emulator of HI maps using Normalizing Flow
    8/26/21, 3:00 PM
  35. 1. Unstructured Section: Problems we can't solve with current tools that we may have a shot with ML

    Chair: Simone Ferraro & Colin Hill

    Go to contribution page

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