research
∙
11/22/2022
Cosmology from Galaxy Redshift Surveys with PointNet
In recent years, deep learning approaches have achieved state-of-the-art...
share
research
∙
03/17/2022
DeepLSS: breaking parameter degeneracies in large scale structure with deep learning analysis of combined probes
In classical cosmological analysis of large scale structure surveys with...
research
∙
04/17/2020
Emulation of cosmological mass maps with conditional generative adversarial networks
Mass maps created using weak gravitational lensing techniques play a cru...
research
∙
08/15/2019
Cosmological N-body simulations: a challenge for scalable generative models
Deep generative models, such as Generative Adversarial Networks (GANs) o...
research
∙
04/08/2019
DeepSphere: towards an equivariant graph-based spherical CNN
Spherical data is found in many applications. By modeling the discretize...
research
∙
10/29/2018
DeepSphere: Efficient spherical Convolutional Neural Network with HEALPix sampling for cosmological applications
Convolutional Neural Networks (CNNs) are a cornerstone of the Deep Learn...
research
∙
01/27/2018
Fast Cosmic Web Simulations with Generative Adversarial Networks
Dark matter in the universe evolves through gravity to form a complex ne...
research
∙
01/23/2018
Fast Point Spread Function Modeling with Deep Learning
Modeling the Point Spread Function (PSF) of wide-field surveys is vital ...
research
∙
07/24/2017
Accelerating Approximate Bayesian Computation with Quantile Regression: Application to Cosmological Redshift Distributions
Approximate Bayesian Computation (ABC) is a method to obtain a posterior...
research
∙
07/17/2017
