189 citations · 582 across the 33 of their papers we have counts for
10 papers · 1 filter
Auto-Calibration of Remote Sensing Solar Telescopes with Deep Learning
Brad Neuberg, Souvik Bose, Valentina Salvatelli +6
As a part of NASA's Heliophysics System Observatory (HSO) fleet of satellites,the Solar Dynamics Observatory (SDO) has continuously monitored the Sun since2010. Ultraviolet (UV) an…
Using U-Nets to Create High-Fidelity Virtual Observations of the Solar Corona
Valentina Salvatelli, Souvik Bose, Brad Neuberg +6
Understanding and monitoring the complex and dynamic processes of the Sun is important for a number of human activities on Earth and in space. For this reason, NASA's Solar Dynamic…
Single-Frame Super-Resolution of Solar Magnetograms: Investigating Physics-Based Metrics & Losses
Anna Jungbluth, Xavier Gitiaux, Shane A. Maloney +7
Breakthroughs in our understanding of physical phenomena have traditionally followed improvements in instrumentation. Studies of the magnetic field of the Sun, and its influence on…
Correlation of Auroral Dynamics and GNSS Scintillation with an Autoencoder
Kara Lamb, Garima Malhotra, Athanasios Vlontzos +7
High energy particles originating from solar activity travel along the the Earth's magnetic field and interact with the atmosphere around the higher latitudes. These interactions o…
Prediction of GNSS Phase Scintillations: A Machine Learning Approach
Kara Lamb, Garima Malhotra, Athanasios Vlontzos +7
A Global Navigation Satellite System (GNSS) uses a constellation of satellites around the earth for accurate navigation, timing, and positioning. Natural phenomena like space weath…
Amortized Rejection Sampling in Universal Probabilistic Programming
Saeid Naderiparizi, Adam Ścibior, Andreas Munk +9
Naive approaches to amortized inference in probabilistic programs with unbounded loops can produce estimators with infinite variance. This is particularly true of importance sampli…
Flood Detection On Low Cost Orbital Hardware
Gonzalo Mateo-Garcia, Silviu Oprea, Lewis Smith +5
Satellite imaging is a critical technology for monitoring and responding to natural disasters such as flooding. Despite the capabilities of modern satellites, there is still much t…
Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale
Atılım Güneş Baydin, Lei Shao, Wahid Bhimji +14
Probabilistic programming languages (PPLs) are receiving widespread attention for performing Bayesian inference in complex generative models. However, applications to science remai…
Hijacking Malaria Simulators with Probabilistic Programming
Bradley Gram-Hansen, Christian Schröder de Witt, Tom Rainforth +3
Epidemiology simulations have become a fundamental tool in the fight against the epidemics of various infectious diseases like AIDS and malaria. However, the complicated and stocha…
An Ensemble of Bayesian Neural Networks for Exoplanetary Atmospheric Retrieval
Adam D. Cobb, Michael D. Himes, Frank Soboczenski +7
Machine learning is now used in many areas of astrophysics, from detecting exoplanets in Kepler transit signals to removing telescope systematics. Recent work demonstrated the pote…