48 citations · 59 across the 6 of their papers we have counts for
4 papers · 1 filter
The Galaxy's Guide to the Tokenizer: A Benchmark for Scientific Foundation Models
Sogol Sanjaripour, Michael J. Smith, Manuel Pérez-Carrasco +3
Tokenization is central to adapting scientific data for transformer-based foundation models, yet its impact on learned representations remains poorly understood. We compare four to…
Domain Adaptation via Minimax Entropy for Real/Bogus Classification of Astronomical Alerts
Guillermo Cabrera-Vives, César Bolivar, Francisco Förster +3
Time domain astronomy is advancing towards the analysis of multiple massive datasets in real time, prompting the development of multi-stream machine learning models. In this work,…
Positional Encodings for Light Curve Transformers: Playing with Positions and Attention
Daniel Moreno-Cartagena, Guillermo Cabrera-Vives, Pavlos Protopapas +3
We conducted empirical experiments to assess the transferability of a light curve transformer to datasets with different cadences and magnitude distributions using various position…
Searching for changing-state AGNs in massive datasets -- I: applying deep learning and anomaly detection techniques to find AGNs with anomalous variability behaviours
P. Sánchez-Sáez, H. Lira, L. Martí +14
The classic classification scheme for Active Galactic Nuclei (AGNs) was recently challenged by the discovery of the so-called changing-state (changing-look) AGNs (CSAGNs). The phys…