arXiv Machine Learning

Classification of Astronomical Spectra Using PCA-Compressed Flux and Inverse-Variance Features

arXiv:2606. 13978v1 Announce Type: cross Abstract: This paper evaluates a signal-processing and supervised-learning pipeline for classifying SDSS DR17 astronomical spectra into stars, galaxies, and quasars.

arXiv AI

5d ago

StarEmbed: Benchmarking Time Series Foundation Models on Astronomical Observations of Variable Stars

arXiv:2510. 06200v4 Announce Type: replace-cross Abstract: Current time series foundation model (TSFM) training corpora largely omit data with certain complexities like irregular temporal sampling.

By Weijian Li, Hong-Yu Chen, Nabeel Rehemtulla, Ved G. Shah, Dongho Kim, Dennis Wu, Qinjie Lin, Adam A. Miller, Han Liu

llms rag benchmarks

arXiv AI

Jun 10

Integral Field Unit Spectroscopy with One Fiber

arXiv:2606. 10197v1 Announce Type: cross Abstract: Integral field unit (IFU) spectroscopy provides spatially resolved spectra across galaxies, offering crucial insights into their evolution.

By Zehao Peng, Biprateep Dey, Chris J. Maddison, Joshua S. Speagle

multimodal

arXiv Machine Learning

Jun 18

Modeling Doppler Shifts in Radial-Velocity Data with Deep Learning toward Earth-mass Exoplanet Detection

arXiv:2606. 18464v1 Announce Type: cross Abstract: Detecting the tiny Doppler shifts induced by Earth-mass planets in stellar radial-velocity measurements remains extremely challenging due to stellar activity.

By Isidro G\'omez-Vargas, Xavier Dumusque, Yinan Zhao, Khaled Al Moulla, Michael Cretignier

arXiv AI

Jun 30

Domain-Informed Multi-View Self-Distillation for Astronomical Light-Curve Representation Learning with JEPA

arXiv:2606. 28446v1 Announce Type: cross Abstract: Light curves describe temporal variations in the brightness of celestial objects.

By Yicheng Rui

rag nlp fine-tuning efficiency benchmarks

arXiv Machine Learning

Jun 24

Efficient reduction of stellar contamination and noise in planetary transmission spectra using neural networks

arXiv:2602. 10330v3 Announce Type: replace-cross Abstract: Context: The characterization of exoplanetary atmospheres has been transformed by the James Webb Space Telescope (JWST), whose infrared sensitivity enables transmission spectroscopy at unprecedented precision.

By David S. Duque-Casta\~no, Lauren Flor-Torres, Jorge I. Zuluaga

safety

arXiv Machine Learning

Jun 26

Transformer-Based Classification of Bacterial Raman Spectra with LOOCV

arXiv:2606. 27096v1 Announce Type: new Abstract: Transformer-based models have recently attracted increasing attention for Raman spectral classification.

By Jamile Mohammad Jafari, Thomas Bocklitz

llms

arXiv Machine Learning

Jun 3

One Transit Is All You Need: Detecting Exoplanets Through Learned Stellar Behaviour with EXOVEIL

arXiv:2606. 02778v1 Announce Type: cross Abstract: I present EXOVEIL, a transit detection system that learns what a star's brightness should look like and flags when reality disagrees.

By Pratik Priyanshu

llms

arXiv Machine Learning

Jul 2

Leveraging Multimodality for Real-Time Classification of Transients and Variables found by the Zwicky Transient Facility

arXiv:2607. 00228v1 Announce Type: cross Abstract: Modern time-domain surveys such as the Zwicky Transient Facility (ZTF) generate hundreds of thousands of alerts each night, making real-time decisions for follow-up observations a central challenge in time-domain astronomy.

By Ved G. Shah, Nabeel Rehemtulla, Adam A. Miller, Sushant Sharma Chaudhary, Michael W. Coughlin, Antoine Le Calloch, Matthew J. Graham, Joahan Castaneda Jaimes, Theophile Jegou du Laz, Ashish A. Mahabal, Frank J. Masci, Josiah Purdum, Reed Riddle, Jesper Sollerman, Anastasia Wei, Mansi M. Kasliwal

efficiency multimodal benchmarks

arXiv Machine Learning

Jul 23

A Deep Learning Framework for Predicting Solar EUV Irradiance During Significant Flares

arXiv:2607. 19597v1 Announce Type: cross Abstract: We present FlareEUV, a multimodal deep learning framework for predicting daily extreme ultraviolet (EUV) irradiance at 6.

By Sathvik Soman, Jason T. L. Wang, Haimin Wang, Haodi Jiang

multimodal

arXiv Machine Learning

Jun 2

21cmEMUv3: a hybrid diffusion-LSTM emulator of 21cmFAST summary observables

arXiv:2606. 00219v1 Announce Type: cross Abstract: We are witnessing a surge in observations of the cosmic dawn (CD) and epoch of reionisation (EoR), driving an increasing demand for fast and robust theoretical interpretation frameworks.

By Daniela Breitman, Andrei Mesinger, Steven G. Murray, Ivan Nikolic, Roberto Trotta

diffusion benchmarks

arXiv Machine Learning

Jun 15

Multi-Variable Stellar Parameter Estimation Using Residual Multitask Neural Networks

arXiv:2606. 13868v1 Announce Type: cross Abstract: We present an end-to-end pipeline for estimating stellar parameters from Sloan Digital Sky Survey Data Release 12 spectra using a fully connected multitask neural network with residual blocks, whose hyperparameters are tuned via Bayesian optimization.

By Bruno Santos Meneses Barreto, Marcio Eisencraft

arXiv Machine Learning

Jun 24

Machine Learning and Deep Learning for Exoplanet Detection and Atmospheric Characterization with JWST and the Upcoming Ariel Mission

arXiv:2606. 23766v1 Announce Type: cross Abstract: The detection and atmospheric characterization of exoplanets have entered a new data-intensive era driven by the James Webb Space Telescope and the upcoming Ariel mission.

By Muallim Yakubu, Vwavware Oruaode Jude

llms diffusion benchmarks safety

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