109 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of MichiganUS36 papers
- University of Tennessee at KnoxvilleUS33 papers
- Georgia State UniversityUS31 papers
- University of Colorado BoulderUS30 papers
- University of Massachusetts AmherstUS29 papers
- Brookhaven National LaboratoryUS28 papers
- Centre National de la Recherche ScientifiqueFR28 papers
- Charles UniversityCZ28 papers
- New Mexico State UniversityUS28 papers
- Vanderbilt UniversityUS28 papers
- Augustana UniversityUS27 papers
- Columbia UniversityUS27 papers
5 papers · 1 filter
Operational reconstruction of Feynman rules for quantum amplitudes via composition algebras
Jens Köplinger, Michael Habeck, Philip Goyal
This article explores an operational model for transition amplitudes between measurements proposed by Goyal et al. within the quantum reconstruction program. To classify suitable a…
Benchmarking Differentially Private Tabular Data Synthesis
Kai Chen, Xiaochen Li, Chen Gong +2
Differentially private (DP) tabular data synthesis generates artificial data that preserves the statistical properties of private data while safeguarding individual privacy. The em…
Measurement of the transverse energy density in Au+Au collisions at GeV with the sPHENIX detector
sPHENIX Collaboration, M. I. Abdulhamid, U. Acharya +302
This paper reports measurements of the transverse energy per unit pseudorapidity () produced in Au+Au collisions at GeV, performed with the sPHENIX…
Modality-Agnostic Style Transfer for Holistic Feature Imputation
Seunghun Baek, Jaeyoon Sim, Mustafa Dere +3
Characterizing a preclinical stage of Alzheimer's Disease (AD) via single imaging is difficult as its early symptoms are quite subtle. Therefore, many neuroimaging studies are cura…
Learning Covariance-Based Multi-Scale Representation of Neuroimaging Measures for Alzheimer Classification
Seunghun Baek, Injun Choi, Mustafa Dere +3
Stacking excessive layers in DNN results in highly underdetermined system when training samples are limited, which is very common in medical applications. In this regard, we presen…