170 citations · 439 across the 14 of their papers we have counts for
7 papers · 1 filter
Flow Matching for Atmospheric Retrieval of Exoplanets: Where Reliability meets Adaptive Noise Levels
Timothy D. Gebhard, Jonas Wildberger, Maximilian Dax +4
Inferring atmospheric properties of exoplanets from observed spectra is key to understanding their formation, evolution, and habitability. Since traditional Bayesian approaches to…
Inferring Atmospheric Properties of Exoplanets with Flow Matching and Neural Importance Sampling
Timothy D. Gebhard, Jonas Wildberger, Maximilian Dax +3
Atmospheric retrievals (AR) characterize exoplanets by estimating atmospheric parameters from observed light spectra, typically by framing the task as a Bayesian inference problem.…
Integrated photonic-based coronagraphic systems for future space telescopes
Niyati Desai, Lorenzo König, Emiel Por +38
The detection and characterization of Earth-like exoplanets around Sun-like stars is a primary science motivation for the Habitable Worlds Observatory. However, the current best te…
Parameterizing pressure-temperature profiles of exoplanet atmospheres with neural networks
Timothy D. Gebhard, Daniel Angerhausen, Björn S. Konrad +3
Atmospheric retrievals (AR) of exoplanets typically rely on a combination of a Bayesian inference technique and a forward simulator to estimate atmospheric properties from an obser…
Half-sibling regression meets exoplanet imaging: PSF modeling and subtraction using a flexible, domain knowledge-driven, causal framework
Timothy D. Gebhard, Markus J. Bonse, Sascha P. Quanz +1
High-contrast imaging of exoplanets hinges on powerful post-processing methods to denoise the data and separate the signal of a companion from its host star, which is typically ord…
Physically constrained causal noise models for high-contrast imaging of exoplanets
Timothy D. Gebhard, Markus J. Bonse, Sascha P. Quanz +1
The detection of exoplanets in high-contrast imaging (HCI) data hinges on post-processing methods to remove spurious light from the host star. So far, existing methods for this tas…
Convolutional neural networks: a magic bullet for gravitational-wave detection?
Timothy D. Gebhard, Niki Kilbertus, Ian Harry +1
In the last few years, machine learning techniques, in particular convolutional neural networks, have been investigated as a method to replace or complement traditional matched fil…