7.7k citations
- Wake Forest University Health SciencesUS20 papers
- Georgia Institute of TechnologyUS15 papers
- Rutgers, The State University of New JerseyUS15 papers
- Los Alamos National LaboratoryUS14 papers
- Universitat de ValènciaES14 papers
- University of WashingtonUS14 papers
- North Carolina State UniversityUS12 papers
- The University of Texas at DallasUS12 papers
- Centre National de la Recherche ScientifiqueFR10 papers
- Goethe University FrankfurtDE10 papers
- Cornell UniversityUS9 papers
- Johns Hopkins UniversityUS9 papers
392 papers
Light Propagation Prescriptions for Black Hole Movies
Daniel Rojas-Paternina, Alejandro Cárdenas-Avendaño
The spatiotemporal content of a black-hole movie is set jointly by source variability and by the distribution of light-travel times across the image. In the slow-light prescription…
Parameter-estimation bias induced by transient orbital resonances in extreme-mass-ratio inspirals
Edoardo Levati, Alejandro Cárdenas-Avendaño
Given the multifrequency nature of relativistic orbits, transient orbital resonances are expected to be ubiquitous during an extreme-mass-ratio inspiral (EMRI). At a resonance, the…
Sensitivities of Black Hole Images from GRMHD Simulations
Pedro Naethe Motta, Mário Raia Neto, Cora Prather +1
The advent of high-fidelity imaging of supermassive black holes calls for efficient and robust data-analysis methods. In this work, we use , a differentiable, $\te…
Gravitational Wave Measurement of the - Intrinsic Scatter at High Redshift
Cayenne Matt, Kayhan Gültekin, Gabriella Agazie +109
The observed GWB spectrum is higher in amplitude than model predictions by a factor of 2-3. Using a semi-analytic model, we evaluate the effect of a high-scatter supermassive black…
Personalized Prediction of Perceived Message Effectiveness Using Large Language Model Based Digital Twins
Jasmin Han, Janardan Devkota, Joseph Waring +8
Perceived message effectiveness (PME) by potential intervention end-users is important for selecting and optimizing personalized smoking cessation intervention messages for mobile…
Interpretable Failure Analysis in Multi-Agent Reinforcement Learning Systems
Risal Shahriar Shefin, Debashis Gupta, Thai Le +1
Multi-Agent Reinforcement Learning (MARL) is increasingly deployed in safety-critical domains, yet methods for interpretable failure detection and attribution remain underdeveloped…