Copertina

Beyond mirkwood: Enhancing SED Modeling with Conformal Predictions

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autore principale:	Gilda, Sankalp
Natura:	Preprint
Pubblicazione:	2023
Soggetti:	Instrumentation and Methods for Astrophysics Astrophysics of Galaxies Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

AstroPT: Scaling Large Observation Models for Astronomy
di: Smith, Michael J., et al.
Pubblicazione: (2024)

Accelerating Redshift-Conditioned Galaxy Image Synthesis with One-step Generative Modeling
di: Yang, Tianyue, et al.
Pubblicazione: (2026)

ProMage: fast galaxy magnitudes emulation combining SED forward-modelling and machine learning
di: Tortorelli, Luca, et al.
Pubblicazione: (2025)

SAGUI: SED-based Segmentation of Multi-band Galaxy Images -- Application to JADES in GOODS-South
di: de Souza, Rafael S., et al.
Pubblicazione: (2026)

Identifying Doppelganger Active Galactic Nuclei across redshifts from spectroscopic surveys
di: Sareen, Shreya, et al.
Pubblicazione: (2025)

Using different sources of ground truths and transfer learning to improve the generalization of photometric redshift estimation
di: Soriano, Jonathan, et al.
Pubblicazione: (2024)

Emulating Radiative Transfer in Astrophysical Environments
di: Rost, Rune, et al.
Pubblicazione: (2025)

Bayesian and Convolutional Networks for Hierarchical Morphological Classification of Galaxies
di: Serrano-Pérez, Jonathan, et al.
Pubblicazione: (2024)

Learning What's Real: Disentangling Signal and Measurement Artifacts in Multi-Sensor Data, with Applications to Astrophysics
di: Mercader-Perez, Pablo, et al.
Pubblicazione: (2026)

PICZL: Image-based Photometric Redshifts for AGN
di: Roster, William, et al.
Pubblicazione: (2024)

Multi-Modal Masked Autoencoders for Learning Image-Spectrum Associations for Galaxy Evolution and Cosmology
di: Himes, Morgan, et al.
Pubblicazione: (2025)

Automatic Machine Learning Framework to Study Morphological Parameters of AGN Host Galaxies within $z < 1.4$ in the Hyper Supreme-Cam Wide Survey
di: Tian, Chuan, et al.
Pubblicazione: (2025)

Galaxy 3D Shape Recovery using Mixture Density Network
di: Yong, Suk Yee, et al.
Pubblicazione: (2024)

OJALÁ: Optimizing J-PAS Astronomy for Large-scale Analysis. A foundation model for the SED of galaxies, QSOs and stars
di: Martínez-Solaeche, G., et al.
Pubblicazione: (2026)

Neural-Network Chemical Emulator for First-Star Formation: Robust Iterative Predictions over a Wide Density Range
di: Ono, Sojun, et al.
Pubblicazione: (2025)

ChronoFlow: A Data-Driven Model for Gyrochronology
di: Van-Lane, Phil R., et al.
Pubblicazione: (2024)

deep-REMAP: Probabilistic Parameterization of Stellar Spectra Using Regularized Multi-Task Learning
di: Gilda, Sankalp
Pubblicazione: (2025)

Using Neural Network Models to Estimate Stellar Ages from Lithium Equivalent Widths: An EAGLES Expansion
di: Weaver, George, et al.
Pubblicazione: (2024)

Euclid: Galaxy SED reconstruction in the PHZ processing function: impact on the PSF and the role of medium-band filters
di: Euclid Collaboration, et al.
Pubblicazione: (2026)

On the functional form of the radial acceleration relation
di: Desmond, Harry, et al.
Pubblicazione: (2023)

Constraining dark matter halo profiles with symbolic regression
di: Martín, Alicia, et al.
Pubblicazione: (2025)

CIGaRS I: Combined simulation-based inference from type Ia supernovae and host photometry
di: Karchev, Konstantin, et al.
Pubblicazione: (2025)

(Exhaustive) Symbolic Regression and model selection by minimum description length
di: Desmond, Harry
Pubblicazione: (2025)

Interpretable machine learning of halo gas density profiles: a sensitivity analysis of cosmological hydrodynamical simulations
di: Sorini, Daniele, et al.
Pubblicazione: (2025)

Disentangling stellar atmospheric parameters in astronomical spectra using Generative Adversarial Neural Networks
di: Manteiga, Minia, et al.
Pubblicazione: (2025)

What ZTF Saw Where Rubin Looked: Anomaly Hunting in DR23
di: Pruzhinskaya, Maria V., et al.
Pubblicazione: (2025)

Unveiling the Power of Uncertainty: A Journey into Bayesian Neural Networks for Stellar dating
di: Tamames-Rodero, Víctor, et al.
Pubblicazione: (2025)

Emulators for stellar profiles in binary population modeling
di: Teng, Elizabeth, et al.
Pubblicazione: (2024)

LtU-ILI: An All-in-One Framework for Implicit Inference in Astrophysics and Cosmology
di: Ho, Matthew, et al.
Pubblicazione: (2024)

3D-PDR Orion dataset and NeuralPDR: Neural Differential Equations for Photodissociation Regions
di: Vermariën, Gijs, et al.
Pubblicazione: (2024)

Machine Learning Methods for Automated Interstellar Object Classification with LSST
di: Cloete, Richard, et al.
Pubblicazione: (2024)

Hubble Astrometry for the Local Group and Beyond in the 2030s
di: Sohn, S. Tony, et al.
Pubblicazione: (2026)

An end-to-end strategy for recovering a free-form potential from a snapshot of stellar coordinates
di: Tenachi, Wassim, et al.
Pubblicazione: (2023)

Class Symbolic Regression: Gotta Fit 'Em All
di: Tenachi, Wassim, et al.
Pubblicazione: (2023)

Galaxy image simplification using Generative AI
di: Erukude, Sai Teja, et al.
Pubblicazione: (2025)

Self-supervised Synthetic Pretraining for Inference of Stellar Mass Embedded in Dense Gas
di: Hirashima, Keiya, et al.
Pubblicazione: (2025)

Neural Network Prediction of Strong Lensing Systems with Domain Adaptation and Uncertainty Quantification
di: Agarwal, Shrihan, et al.
Pubblicazione: (2024)

SHARP: Beyond JWST -- Revealing the galaxy birth and growth with the resolution of the ELT
di: Saracco, P., et al.
Pubblicazione: (2025)

Beyond radial profiles: Using log-normal distributions to model the multiphase circumgalactic medium
di: Dutta, Alankar, et al.
Pubblicazione: (2023)

Beyond Colors: Probing Redshifts from Galaxy Morphology in Single-band Images with ViT-MDNz
di: Luo, Zhijian, et al.
Pubblicazione: (2026)