178 citations
- California Institute of TechnologyUS4 papers
- Fermi National Accelerator LaboratoryUS4 papers
- University of MichiganUS4 papers
- Astrobiology CenterJP3 papers
- Astronomy and SpaceAU3 papers
- Center for Astrophysics Harvard & SmithsonianUS3 papers
- Institute for Fundamental Physics of the UniverseIT3 papers
- Institute of AstronomyRU3 papers
- Kavli Institute for Particle Astrophysics and CosmologyUS3 papers
- Netherlands Institute for Radio AstronomyNL3 papers
- Space Telescope Science InstituteUS3 papers
- Technion – Israel Institute of TechnologyIL3 papers
5 papers · 2 filters
Why Machine Learning Models Systematically Underestimate Extreme Values II: How to Fix It with LatentNN
Yuan-Sen Ting
Attenuation bias -- the systematic underestimation of regression coefficients due to measurement errors in input variables -- affects astronomical data-driven models. For linear re…
Derivative-Aligned Anticipation of Forbush Decreases from Entropy and Fractal Markers
Juan D. Perez-Navarro, D. Sierra-Porta
We develop a feature-based framework to anticipate Forbush decreases in one-minute neutron-monitor records by tracking sliding-window invariants from information theory, scaling, a…
A novel algorithm for GPU-accelerated particle-mesh interactions implemented in the QUOKKA code
Chong-Chong He, Benjamin D. Wibking, Aditi Vijayan +2
We present a novel, GPU-optimized algorithm for particle-mesh interactions in grid-based hydrodynamics simulations, designed for massively parallel architectures. This approach ove…
Probing Stellar Kinematics with the Time-Asymmetric Hanbury Brown and Twiss Effect
Lucijana Stanic, Ivan Cardea, Edoardo Charbon +11
Intensity interferometry (II) offers a powerful means to observe stellar objects with a high resolution. In this work, we demonstrate that II can also probe internal stellar kinema…
A Semi-Supervised Learning Method for the Identification of Bad Exposures in Large Imaging Surveys
Yufeng Luo, Adam D. Myers, Alex Drlica-Wagner +7
As the data volume of astronomical imaging surveys rapidly increases, traditional methods for image anomaly detection, such as visual inspection by human experts, are becoming impr…