50 citations · 122 across the 6 of their papers we have counts for
6 papers
Fast and efficient identification of anomalous galaxy spectra with neural density estimation
Vanessa Böhm, Alex G. Kim, Stéphanie Juneau
Current large-scale astrophysical experiments produce unprecedented amounts of rich and diverse data. This creates a growing need for fast and flexible automated data inspection me…
Probabilistic Autoencoder
Vanessa Böhm, Uroš Seljak
Principal Component Analysis (PCA) minimizes the reconstruction error given a class of linear models of fixed component dimensionality. Probabilistic PCA adds a probabilistic struc…
Bayesian weak lensing tomography: Reconstructing the 3D large-scale distribution of matter with a lognormal prior
Vanessa Böhm, Stefan Hilbert, Maksim Greiner +1
We present a Bayesian reconstruction algorithm that infers the three-dimensional large-scale matter distribution from the weak gravitational lensing effects measured in the image s…
Cosmic expansion history from SNe Ia data via information field theory -- the charm code
Natàlia Porqueres, Torsten A. Enßlin, Maksim Greiner +4
We present charm (cosmic history agnostic reconstruction method), a novel inference algorithm that reconstructs the cosmic expansion history as encoded in the Hubble parameter $H(z…
CMB Lensing Beyond the Power Spectrum: Cosmological Constraints from the One-Point PDF and Peak Counts
Jia Liu, J. Colin Hill, Blake D. Sherwin +3
Unprecedentedly precise cosmic microwave background (CMB) data are expected from ongoing and near-future CMB Stage-III and IV surveys, which will yield reconstructed CMB lensing ma…
Signal inference with unknown response: Calibration-uncertainty renormalized estimator
Sebastian Dorn, Torsten A. Enßlin, Maksim Greiner +2
The calibration of a measurement device is crucial for every scientific experiment, where a signal has to be inferred from data. We present CURE, the calibration uncertainty renorm…