activity
20162020
most citedFinding Patient Zero: Learning Contagion Source with Graph Neural Networks

28 citations · 76 across the 3 of their papers we have counts for

collaborators

6 papers

cs.SI202028 cited

Finding Patient Zero: Learning Contagion Source with Graph Neural Networks

Chintan Shah, Nima Dehmamy, Nicola Perra +4

Locating the source of an epidemic, or patient zero (P0), can provide critical insights into the infection's transmission course and allow efficient resource allocation. Existing m…

cs.LG2020

Multiresolution Tensor Learning for Efficient and Interpretable Spatial Analysis

Jung Yeon Park, Kenneth Theo Carr, Stephan Zheng +2

Efficient and interpretable spatial analysis is crucial in many fields such as geology, sports, and climate science. Tensor latent factor models can describe higher-order correlati…

physics.comp-ph2019

Towards Physics-informed Deep Learning for Turbulent Flow Prediction

Rui Wang, Karthik Kashinath, Mustafa Mustafa +2

While deep learning has shown tremendous success in a wide range of domains, it remains a grand challenge to incorporate physical principles in a systematic manner to the design, t…

cs.LG201721 cited

Tensor Regression Meets Gaussian Processes

Rose Yu, Guangyu Li, Yan Liu

Low-rank tensor regression, a new model class that learns high-order correlation from data, has recently received considerable attention. At the same time, Gaussian processes (GP)…

cs.LG201627 cited

Learning from Multiway Data: Simple and Efficient Tensor Regression

Rose Yu, Yan Liu

Tensor regression has shown to be advantageous in learning tasks with multi-directional relatedness. Given massive multiway data, traditional methods are often too slow to operate…

cs.LG2016

A Survey on Social Media Anomaly Detection

Rose Yu, Huida Qiu, Zhen Wen +2

Social media anomaly detection is of critical importance to prevent malicious activities such as bullying, terrorist attack planning, and fraud information dissemination. With the…