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Machine Learning and Cosmology

Machine Learning and Cosmology

15 March 2022
C. Dvorkin
S. Mishra-Sharma
Brian D. Nord
V. A. Villar
Camille Avestruz
K. Bechtol
A. Ćiprijanović
Andrew J. Connolly
L. Garrison
G. Narayan
F. Villaescusa-Navarro
    AI4CE
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Papers citing "Machine Learning and Cosmology"

7 / 7 papers shown
Title
Constraining cosmological parameters from N-body simulations with
  Variational Bayesian Neural Networks
Constraining cosmological parameters from N-body simulations with Variational Bayesian Neural Networks
Héctor J. Hortúa
L. '. García
Leonardo Castañeda C.
BDL
24
4
0
09 Jan 2023
CP-PINNs: Data-Driven Changepoints Detection in PDEs Using Online
  Optimized Physics-Informed Neural Networks
CP-PINNs: Data-Driven Changepoints Detection in PDEs Using Online Optimized Physics-Informed Neural Networks
Zhi-Ling Dong
Pawel Polak
PINN
19
1
0
18 Aug 2022
Inferring dark matter substructure with astrometric lensing beyond the
  power spectrum
Inferring dark matter substructure with astrometric lensing beyond the power spectrum
S. Mishra-Sharma
35
11
0
04 Oct 2021
The CAMELS Multifield Dataset: Learning the Universe's Fundamental
  Parameters with Artificial Intelligence
The CAMELS Multifield Dataset: Learning the Universe's Fundamental Parameters with Artificial Intelligence
F. Villaescusa-Navarro
S. Genel
D. Anglés-Alcázar
L. Thiele
R. Davé
...
Luis Fernando Machado Poletti Valle
L. A. Perez
D. Nagai
N. Battaglia
M. Vogelsberger
19
47
0
22 Sep 2021
Multifield Cosmology with Artificial Intelligence
Multifield Cosmology with Artificial Intelligence
F. Villaescusa-Navarro
D. Anglés-Alcázar
S. Genel
D. Spergel
Yin Li
...
Sultan Hassan
J. Z. Matilla
D. Narayanan
R. Davé
M. Vogelsberger
AI4CE
33
20
0
20 Sep 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
270
5,660
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
282
9,136
0
06 Jun 2015
1