29 citations · 41 across the 7 of their papers we have counts for
7 papers
PANDA: Expanded Width-Aware Message Passing Beyond Rewiring
Jeongwhan Choi, Sumin Park, Hyowon Wi +2
Recent research in the field of graph neural network (GNN) has identified a critical issue known as "over-squashing," resulting from the bottleneck phenomenon in graph structures,…
QoS-Aware Graph Contrastive Learning for Web Service Recommendation
Jeongwhan Choi, Duksan Ryu
With the rapid growth of cloud services driven by advancements in web service technology, selecting a high-quality service from a wide range of options has become a complex task. T…
Long-term Time Series Forecasting based on Decomposition and Neural Ordinary Differential Equations
Seonkyu Lim, Jaehyeon Park, Seojin Kim +5
Long-term time series forecasting (LTSF) is a challenging task that has been investigated in various domains such as finance investment, health care, traffic, and weather forecasti…
Graph Neural Rough Differential Equations for Traffic Forecasting
Jeongwhan Choi, Noseong Park
Traffic forecasting is one of the most popular spatio-temporal tasks in the field of machine learning. A prevalent approach in the field is to combine graph convolutional networks…
Prediction-based One-shot Dynamic Parking Pricing
Seoyoung Hong, Heejoo Shin, Jeongwhan Choi +1
Many U.S. metropolitan cities are notorious for their severe shortage of parking spots. To this end, we present a proactive prediction-driven optimization framework to dynamically…
Linear, or Non-Linear, That is the Question!
Taeyong Kong, Taeri Kim, Jinsung Jeon +4
There were fierce debates on whether the non-linear embedding propagation of GCNs is appropriate to GCN-based recommender systems. It was recently found that the linear embedding p…