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Found 4 papers, 3 papers with code
SuperBench: A Super-Resolution Benchmark Dataset for Scientific Machine Learning
Super-Resolution (SR) techniques aim to enhance data resolution, enabling the retrieval of finer details, and improving the overall quality and fidelity of the data representation.
Self-supervised similarity search for large scientific datasets
We present the use of self-supervised learning to explore and exploit large unlabeled datasets.
Mining for Strong Gravitational Lenses with Self-supervised Learning
We employ self-supervised representation learning to distill information from 76 million galaxy images from the Dark Energy Spectroscopic Instrument Legacy Imaging Surveys' Data Release 9.
Cosmic Inference: Constraining Parameters With Observations and Highly Limited Number of Simulations
Cosmological probes pose an inverse problem where the measurement result is obtained through observations, and the objective is to infer values of model parameters which characterize the underlying physical system -- our Universe.
Instrumentation and Methods for Astrophysics Cosmology and Nongalactic Astrophysics
