Daniel Angerhausen

According to our database, Daniel Angerhausen authored at least 8 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Automated Discovery of Anomalous Features in Ultralarge Planetary Remote-Sensing Datasets Using Variational Autoencoders.

Adam Lesnikowski, Valentin Tertius Bickel, Daniel Angerhausen

IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024

Flow Matching for Atmospheric Retrieval of Exoplanets: Where Reliability meets Adaptive Noise Levels.

Timothy D. Gebhard, Jonas Wildberger, Maximilian Dax, Annalena Kofler, Daniel Angerhausen, Sascha P. Quanz, Bernhard Schölkopf

CoRR, 2024

2023

Inferring Atmospheric Properties of Exoplanets with Flow Matching and Neural Importance Sampling.

Timothy D. Gebhard, Jonas Wildberger, Maximilian Dax, Daniel Angerhausen, Sascha P. Quanz, Bernhard Schölkopf

CoRR, 2023

Parameterizing pressure-temperature profiles of exoplanet atmospheres with neural networks.

Timothy D. Gebhard, Daniel Angerhausen, Björn S. Konrad, Eleonora Alei, Sascha P. Quanz, Bernhard Schölkopf

CoRR, 2023

2020

Unsupervised Distribution Learning for Lunar Surface Anomaly Detection.

Adam Lesnikowski, Valentin Tertius Bickel, Daniel Angerhausen

CoRR, 2020

2019

An Ensemble of Bayesian Neural Networks for Exoplanetary Atmospheric Retrieval.

Adam D. Cobb, Michael D. Himes, Frank Soboczenski, Simone Zorzan, Molly D. O'Beirne, Atilim Günes Baydin, Yarin Gal, Shawn D. Domagal-Goldman, Giada N. Arney, Daniel Angerhausen

CoRR, 2019

2018

Bayesian Deep Learning for Exoplanet Atmospheric Retrieval.

Frank Soboczenski, Michael D. Himes, Molly D. O'Beirne, Simone Zorzan, Atilim Gunes Baydin, Adam D. Cobb, Daniel Angerhausen, Giada N. Arney, Shawn D. Domagal-Goldman

CoRR, 2018

2017

EXONEST: The Bayesian Exoplanetary Explorer.

Kevin H. Knuth, Ben Placek, Daniel Angerhausen, Jennifer L. Carter, Bryan D'Angelo, Anthony D. Gai, Bertrand Carado

Entropy, 2017