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Found 7 papers, 2 papers with code
A Perspective on Deep Vision Performance with Standard Image and Video Codecs
The use of standardized codecs, such as JPEG or H. 264, is prevalent and required to ensure interoperability.
A deep learning framework for jointly extracting spectra and source-count distributions in astronomy
Astronomical observations typically provide three-dimensional maps, encoding the distribution of the observed flux in (1) the two angles of the celestial sphere and (2) energy/frequency.
Stochastic Super-resolution of Cosmological Simulations with Denoising Diffusion Models
In recent years, deep learning models have been successfully employed for augmenting low-resolution cosmological simulations with small-scale information, a task known as "super-resolution".
Semantic Self-adaptation: Enhancing Generalization with a Single Sample
The lack of out-of-domain generalization is a critical weakness of deep networks for semantic segmentation.
Adaptive Generalization for Semantic Segmentation
In this work, we empirically study an adaptive inference strategy for semantic segmentation that adjusts the model to the test sample before producing the final prediction.
Quantifying the impact of baryon-CDM perturbations on halo clustering and baryon fraction
Using gravity-only 2-fluid simulations we assess the impact of such perturbations on the dark matter halos distribution.
Cosmology and Nongalactic Astrophysics
Unveiling the singular dynamics in the cosmic large-scale structure
It is known that the gravitational collapse of cold dark matter leads to infinite-density caustics that seed the primordial dark-matter halos in the large-scale structure.
Cosmology and Nongalactic Astrophysics Adaptation and Self-Organizing Systems
