18 citations · 25 across the 8 of their papers we have counts for
8 papers
Spectral and Spatial Graph Learning for Multispectral Solar Image Compression
Prasiddha Siwakoti, Atefeh Khoshkhahtinat, Piyush M. Mehta +3
High-fidelity compression of multispectral solar imagery remains challenging for space missions, where limited bandwidth must be balanced against preserving fine spectral and spati…
Diffusion Modeling of the Three-Dimensional Magnetic Field in the Sun's Corona
Daniel E. da Silva, Michael Kirk, Nat Mathews +1
In this work, we introduce a novel generative denoising diffusion model for synthesizing the Sun's three-dimensional coronal magnetic field, a complex and dynamic region characteri…
Neural-based Video Compression on Solar Dynamics Observatory Images
Atefeh Khoshkhahtinat, Ali Zafari, Piyush M. Mehta +4
NASA's Solar Dynamics Observatory (SDO) mission collects extensive data to monitor the Sun's daily activity. In the realm of space mission design, data compression plays a crucial…
Neural-based Compression Scheme for Solar Image Data
Ali Zafari, Atefeh Khoshkhahtinat, Jeremy A. Grajeda +6
Studying the solar system and especially the Sun relies on the data gathered daily from space missions. These missions are data-intensive and compressing this data to make them eff…
Multi-spectral Entropy Constrained Neural Compression of Solar Imagery
Ali Zafari, Atefeh Khoshkhahtinat, Piyush M. Mehta +4
Missions studying the dynamic behaviour of the Sun are defined to capture multi-spectral images of the sun and transmit them to the ground station in a daily basis. To make transmi…
Context-Aware Neural Video Compression on Solar Dynamics Observatory
Atefeh Khoshkhahtinat, Ali Zafari, Piyush M. Mehta +4
NASA's Solar Dynamics Observatory (SDO) mission collects large data volumes of the Sun's daily activity. Data compression is crucial for space missions to reduce data storage and v…
Deep Learning for Space Weather Prediction: Bridging the Gap between Heliophysics Data and Theory
John C. Dorelli, Chris Bard, Thomas Y. Chen +11
Traditionally, data analysis and theory have been viewed as separate disciplines, each feeding into fundamentally different types of models. Modern deep learning technology is begi…
Identifying Flux Rope Signatures Using a Deep Neural Network
Luiz F. G. dos Santos, Ayris Narock, Teresa Nieves-Chinchilla +2
Among the current challenges in Space Weather, one of the main ones is to forecast the internal magnetic configuration within Interplanetary Coronal Mass Ejections (ICMEs). Current…