10 citations · 33 across the 16 of their papers we have counts for
7 papers · 1 filter
Learning Radio Astronomical Representations with LeJEPA and Very Small Models
Erica Lastufka, Mariia Drozdova, Vitaliy Kinakh +4
Representations learned by vision foundation models pretrained on natural images have been shown to be useful for out-of-domain astronomical images. Performance on scientific downs…
DINOspec: Efficient Multimodal Alignment of Vision and Spectral Foundation Models for Astronomy
Erica Lastufka, Mariia Drozdova, Daniel Schaerer +1
Astronomical observations provide multimodal views of physical systems, with images and spectra capturing complementary properties of celestial objects. Scientific foundation model…
Exploring Image-Text Alignment for Radio Galaxy Morphologies
Erica Lastufka, Mariia Drozdova, Svyatoslav Volosynovskiy
We investigate whether specially constructed text captions can capture the same morphological information as radio galaxy images. Using the MiraBest dataset, we generate captions w…
Radio Astronomy in the Era of Vision-Language Models: Prompt Sensitivity and Adaptation
Mariia Drozdova, Erica Lastufka, Vitaliy Kinakh +3
Vision-Language Models (VLMs), such as recent Qwen and Gemini models, are positioned as general-purpose AI systems capable of reasoning across domains. Yet their capabilities in sc…
Bridging the Gap: Examining Vision Foundation Models for Optical and Radio Astronomy Applications
E. Lastufka, O. Bait, M. Drozdova +7
Vision foundation models, which have demonstrated significant potential in many multimedia applications, are often underutilized in the natural sciences. This is primarily due to m…
Self-Supervised Learning on MeerKAT Wide-Field Continuum Images
Erica Lastufka, Omkar Bait, Olga Taran +8
Self-supervised learning (SSL) applied to natural images has demonstrated a remarkable ability to learn meaningful, low-dimension representations without labels, resulting in model…
Radio-astronomical Image Reconstruction with Conditional Denoising Diffusion Model
Mariia Drozdova, Vitaliy Kinakh, Omkar Bait +6
Reconstructing sky models from dirty radio images for accurate source localization and flux estimation is crucial for studying galaxy evolution at high redshift, especially in deep…