58 citations · 108 across the 4 of their papers we have counts for
6 papers
When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning
Chuizheng Meng, Sungyong Seo, Defu Cao +2
Physics-informed machine learning (PIML), referring to the combination of prior knowledge of physics, which is the high level abstraction of natural phenomenons and human behaviour…
Network Inference from a Mixture of Diffusion Models for Fake News Mitigation
Karishma Sharma, Xinran He, Sungyong Seo +1
The dissemination of fake news intended to deceive people, influence public opinion and manipulate social outcomes, has become a pressing problem on social media. Moreover, informa…
COVID-19 on Social Media: Analyzing Misinformation in Twitter Conversations
Karishma Sharma, Sungyong Seo, Chuizheng Meng +2
The ongoing Coronavirus (COVID-19) pandemic highlights the inter-connectedness of our present-day globalized world. With social distancing policies in place, virtual communication…
A Deep Structural Model for Analyzing Correlated Multivariate Time Series
Changwei Hu, Yifan Hu, Sungyong Seo
Multivariate time series are routinely encountered in real-world applications, and in many cases, these time series are strongly correlated. In this paper, we present a deep learni…
Differentiable Physics-informed Graph Networks
Sungyong Seo, Yan Liu
While physics conveys knowledge of nature built from an interplay between observations and theory, it has been considered less importantly in deep neural networks. Especially, ther…
Social Bots for Online Public Health Interventions
Ashok Deb, Anuja Majmundar, Sungyong Seo +5
According to the Center for Disease Control and Prevention, in the United States hundreds of thousands initiate smoking each year, and millions live with smoking-related dis- eases…