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Likelihood-Free Inference Workshop

Mar 18 – 22, 2019
162 Fifth Ave.
America/New_York timezone

Contribution List

29 out of 29 displayed
  1. 7. Kyle Cranmer
    3/18/19, 9:30 AM
  2. 15. George Papamakarios: Density estimation for LFI
    3/18/19, 11:00 AM
  3. 16. Johann Brehmer: "Mining gold" from implicit models to improve likelihood-free inference
    3/18/19, 12:00 PM
  4. 18. Jan-Matthis Luekmann: Statistical methods for mechanistic models in neuroscience
    3/18/19, 2:00 PM
  5. 17. Owen Thomas: BOLFI and LIFRE
    3/18/19, 2:30 PM
  6. 6. Umberto Simola: Machine Learning Accelerated Likelihood-Free Event Reconstruction in Dark Matter Direct Detection
    3/18/19, 3:00 PM
  7. 19. Rajesh Ranganath
    3/18/19, 4:00 PM
  8. 20. Discussion Time
    3/18/19, 4:30 PM
  9. 21. Tom Charnock: IMNN for dimensionality reduction
    3/19/19, 9:30 AM
  10. 22. Pablo de Castro Manzano: INFERNO: Inference-Aware Neural Optimisation (REMOTE)
    3/19/19, 10:00 AM
  11. 23. Will Handley: Compromise-free Bayesian sparse reconstruction
    3/19/19, 11:00 AM
  12. 24. Ann Lee: Validation of Emulators and Approximate Likelihood Models
    3/19/19, 11:30 AM
  13. 25. Danley Hsu: Estimating Exoplanet Occurrence Rates Using Approximate Bayesian Computation
    3/19/19, 12:00 PM
  14. 26. Nesar Ramachandra: Suite of Gaussian Process emulators for cosmological inference problems
    3/19/19, 2:00 PM
  15. 27. Chieh-An Lin: Simulate a universe on your laptop
    3/19/19, 2:30 PM
  16. 12. Stephen Feeney: TSZ PDF LFI
    3/19/19, 3:00 PM
  17. 28. Henri Pesonen: ELFI - Engine for Likelihood-free Inference
    3/19/19, 4:00 PM
  18. 29. Discussion Time
    3/19/19, 4:30 PM
  19. 11. Ann Lee: Validation of Emulators and Approximate Likelihood Models
  20. 4. Chieh-An Lin: Simulate a universe on your laptop
  21. 1. Danley Hsu: Estimating Exoplanet Occurrence Rates Using Approximate Bayesian Computation
  22. 8. George Papamakarios: Density estimation for LFI
  23. 14. Henri Pesonen: ELFI - Engine for Likelihood-free Inference
  24. 9. Jan-Matthis Luekmann: Statistical methods for mechanistic models in neuroscience
  25. 10. Johann Brehmer: "Mining gold" from implicit models to improve likelihood-free inference
  26. 5. Nesar Ramachandra: Suite of Gaussian Process emulators for cosmological inference problems
  27. 2. Pablo de Castro Manzano: INFERNO: Inference-Aware Neural Optimisation
  28. 3. Tom Charnock: IMNN for dimensionality reduction
  29. 13. Will Handley: Compromise-free Bayesian sparse reconstruction