Hugging Face Trending Papers November 3, 2026

Feature-Based and Deep Learning Methods for Astronomical Light Curve Classification

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arXiv AI

Aug 14

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 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

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

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

arXiv Machine Learning

Jun 2

Probabilistic Data-Driven Modelling of Astrophysical Transients: The Neural Process Family for Ultrafast and Class-Agnostic Light Curve Reconstruction with NightLANP

arXiv:2605. 27527v2 Announce Type: replace-cross Abstract: Astrophysical observations from Earth are subject to weather, environmental, and scientific constraints that lead to sparse, irregular light curves.

By Siddharth Chaini, Federica B. Bianco, Ashish Mahabal

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

One email a morning, machine-written

Related stories

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

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

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

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

Probabilistic Data-Driven Modelling of Astrophysical Transients: The Neural Process Family for Ultrafast and Class-Agnostic Light Curve Reconstruction with NightLANP

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