- Heidelberg UniversityDE2 papers
- ARC Centre of Excellence for All-sky AstrophysicsAU1 paper
- Arcetri Astrophysical ObservatoryIT1 paper
- Australian National UniversityAU1 paper
- Canadian Institute for Theoretical AstrophysicsCA1 paper
- Center for Astrophysics Harvard & SmithsonianUS1 paper
- Centre de Recherche Astrophysique de LyonFR1 paper
- École de Technologie SupérieureCA1 paper
- Environment and Climate Change CanadaCA1 paper
- European Southern ObservatoryCL1 paper
- Forschungsstätte der Evangelischen StudiengemeinschaftDE1 paper
- International Centre for Radio Astronomy ResearchAU1 paper
5 papers
XMix: Combating Extremely Noisy Labels via Local Smoothness in Self-Supervised Feature Space
Chengqi Li, Yangdi Lu, Zhihao Shi +3
Supervised deep learning models rely on large, accurately labeled datasets, yet noisy annotations are often unavoidable and can severely degrade performance under high noise levels…
The PHANGS-AstroSat Atlas of Nearby Star Forming Galaxies
Hamid Hassani, Erik Rosolowsky, Eric W. Koch +29
We present the Physics at High Angular resolution in Nearby GalaxieS (PHANGS)-AstroSat atlas, which contains ultraviolet imaging of 31 nearby star-forming galaxies captured by the…
A Maxwell Fish-Eye Lens in a Bose-Einstein Condensate
Jelte Duchêne, Elinor Kath, Floriane Arrouas +7
We experimentally realize an analogue of the optical Maxwell fish-eye lens (MFEL) using phononic excitations in a Bose-Einstein condensate (BEC). A MFEL is characterized by a radia…
A Comparative Study of Student Perspectives on Technical Writing Feedback Quality: Evaluating LLMs, SLMs, and Humans in Computer Science Topics
Suqing Liu, Runlong Ye, Christopher Eaton +2
To address the scalability of feedback in computer science while mitigating the privacy and cost limitations of commercial Large Language Models (LLMs), this study evaluates a loca…
Self-Supervised Tree-level Biomass Estimation in Urban Environments From Airborne LiDAR and Optical Observations
Jose Bermudez, Zilong Zhong, Dominic Cyr +2
Urban tree biomass remains less spatially explicitly quantified than biomass in managed forests because many estimates rely on inventories or coarse products that cannot resolve in…