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Found 5 papers, 2 papers with code
Sum-of-Parts Models: Faithful Attributions for Groups of Features
An explanation of a machine learning model is considered "faithful" if it accurately reflects the model's decision-making process.
Transformers for scientific data: a pedagogical review for astronomers
The deep learning architecture associated with ChatGPT and related generative AI products is known as transformers.
Photo-zSNthesis: Converting Type Ia Supernova Lightcurves to Redshift Estimates via Deep Learning
Upcoming photometric surveys will discover tens of thousands of Type Ia supernovae (SNe Ia), vastly outpacing the capacity of our spectroscopic resources.
A Convolutional Neural Network Approach to Supernova Time-Series Classification
Retrospective classification is used to differentiate cosmologically useful Type Ia SNe from other SN types, and this method achieves >99% accuracy on this task.
What's the Difference? The potential for Convolutional Neural Networks for transient detection without template subtraction
We present a study of the potential for Convolutional Neural Networks (CNNs) to enable separation of astrophysical transients from image artifacts, a task known as "real-bogus" classification without requiring a template subtracted (or difference) image which requires a computationally expensive process to generate, involving image matching on small spatial scales in large volumes of data.
