A CNN with attention and shared latent space recovers SFHs and metallicities from spectro-photometric data with ~0.12 dex age and ~0.03 dex metallicity dispersion while running thousands of times faster than full spectral fitting.
Title resolution pending
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
A new cylindrical cosmological simulation method with radially varying resolution enables self-consistent N-body evolution in S¹×ℝ² topology for systems mismatched to cubic periodicity.
High-resolution molecular gas observations show that spiral arms and bars in z~1.5 disk galaxies drive substantial radial inflows at rates matching star formation, linking morphology directly to gas transport.
citing papers explorer
-
Determining star formation histories and age-metallicity relations with convolutional neural networks
A CNN with attention and shared latent space recovers SFHs and metallicities from spectro-photometric data with ~0.12 dex age and ~0.03 dex metallicity dispersion while running thousands of times faster than full spectral fitting.
-
Cylindrical cosmological simulations with StePS
A new cylindrical cosmological simulation method with radially varying resolution enables self-consistent N-body evolution in S¹×ℝ² topology for systems mismatched to cubic periodicity.
-
NOEMA3D: Resolving radial gas flows in disk galaxies at z~1.1-1.6 with high-resolution CO observations
High-resolution molecular gas observations show that spiral arms and bars in z~1.5 disk galaxies drive substantial radial inflows at rates matching star formation, linking morphology directly to gas transport.