output
20142024
most citedParameterized Explainer for Graph Neural Network

213 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions

7 papers

quant-ph2024

Chaos-Mediated Quantum State Discrimination Near Unit Fidelity

Sourav Paul, Anant Vijay Varma, Yogesh N. Joglekar +1

We investigate a ''quantum microscope'' for qubits based on nonlinear discrete-time chaotic dynamics, which exponentially amplifies the initially small fidelity of a pair of states…

physics.soc-ph2023★ 6 cited

Economical-Epidemiological Analysis of the Coffee Trees Rust Pandemic

Teddy Lazebnik, Ariel Rosenfeld, Labib Shami

Coffee leaf rust is a prevalent botanical disease that causes a worldwide reduction in coffee supply and its quality, leading to immense economic losses. While several pandemic int…

physics.med-ph2022★ 1 cited

Deep Learning-based Protoacoustic Signal Denoising for Proton Range Verification

Jing Wang, James J. Sohn, Yang Lei +5

Objective: Proton therapy offers an advantageous dose distribution compared to the photon therapy, since it deposits most of the energy at the end of range, namely the Bragg peak (…

cs.LG2022

Deep Q-learning of global optimizer of multiply model parameters for viscoelastic imaging

Hongmei Zhang, Kai Wang, Yan Zhou +4

Objective: Estimation of the global optima of multiple model parameters is valuable in imaging to form a reliable diagnostic image. Given non convexity of the objective function, i…

eess.IV2021

Cell abundance aware deep learning for cell detection on highly imbalanced pathological data

Yeman Brhane Hagos, Catherine SY Lecat, Dominic Patel +5

Automated analysis of tissue sections allows a better understanding of disease biology and may reveal biomarkers that could guide prognosis or treatment selection. In digital patho…

cs.LG2020★ 213 cited

Parameterized Explainer for Graph Neural Network

Dongsheng Luo, Wei Cheng, Dongkuan Xu +4

Despite recent progress in Graph Neural Networks (GNNs), explaining predictions made by GNNs remains a challenging open problem. The leading method independently addresses the loca…

stat.AP2014

Leveraging local identity-by-descent increases the power of case/control GWAS with related individuals

Joshua N. Sampson, Bill Wheeler, Peng Li +1

Large case/control Genome-Wide Association Studies (GWAS) often include groups of related individuals with known relationships. When testing for associations at a given locus, curr…