550 citations · 718 across the 45 of their papers we have counts for
6 papers · 1 filter
DPM: A Novel Training Method for Physics-Informed Neural Networks in Extrapolation
Jungeun Kim, Kookjin Lee, Dongeun Lee +2
We present a method for learning dynamics of complex physical processes described by time-dependent nonlinear partial differential equations (PDEs). Our particular interest lies in…
A Sweet Rabbit Hole by DARCY: Using Honeypots to Detect Universal Trigger's Adversarial Attacks
Thai Le, Noseong Park, Dongwon Lee
The Universal Trigger (UniTrigger) is a recently-proposed powerful adversarial textual attack method. Utilizing a learning-based mechanism, UniTrigger generates a fixed phrase that…
SHIELD: Defending Textual Neural Networks against Multiple Black-Box Adversarial Attacks with Stochastic Multi-Expert Patcher
Thai Le, Noseong Park, Dongwon Lee
Even though several methods have proposed to defend textual neural network (NN) models against black-box adversarial attacks, they often defend against a specific text perturbation…
Two-stage Training of Graph Neural Networks for Graph Classification
Manh Tuan Do, Noseong Park, Kijung Shin
Graph neural networks (GNNs) have received massive attention in the field of machine learning on graphs. Inspired by the success of neural networks, a line of research has been con…
Human Mobility during COVID-19 in the Context of Mild Social Distancing: Implications for Technological Interventions
Myeong Lee, Seongkyu Lee, Seonghoon Kim +1
The COVID-19 pandemic has brought both tangible and intangible damage to our society. Many researchers studied about its societal impacts in the countries that had implemented stro…
MONSTOR: An Inductive Approach for Estimating and Maximizing Influence over Unseen Networks
Jihoon Ko, Kyuhan Lee, Kijung Shin +1
Influence maximization (IM) is one of the most important problems in social network analysis. Its objective is to find a given number of seed nodes that maximize the spread of info…