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20182026
most citedA Deep Learning Approach for Forecasting Air Pollution in South Korea Using LSTM

59 citations · 83 across the 17 of their papers we have counts for

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Showing cs.LGShow all

7 papers · 1 filter

cs.LG2026★ 1 cited

IgPose: A Generative Data-Augmented Pipeline for Robust Immunoglobulin-Antigen Binding Prediction

Tien-Cuong Bui, Injae Chung, Wonjun Lee +2

Predicting immunoglobulin-antigen (Ig-Ag) binding remains a significant challenge due to the paucity of experimentally-resolved complexes and the limited accuracy of de novo Ig str…

cs.LG2023★ 1 cited

VeML: An End-to-End Machine Learning Lifecycle for Large-scale and High-dimensional Data

Van-Duc Le, Tien-Cuong Bui, Wen-Syan Li

An end-to-end machine learning (ML) lifecycle consists of many iterative processes, from data preparation and ML model design to model training and then deploying the trained model…

cs.LG2022

INGREX: An Interactive Explanation Framework for Graph Neural Networks

Tien-Cuong Bui, Van-Duc Le, Wen-Syan Li +1

Graph Neural Networks (GNNs) are widely used in many modern applications, necessitating explanations for their decisions. However, the complexity of GNNs makes it difficult to expl…

cs.LG2022★ 1 cited

Toward Multiple Specialty Learners for Explaining GNNs via Online Knowledge Distillation

Tien-Cuong Bui, Van-Duc Le, Wen-syan Li +1

Graph Neural Networks (GNNs) have become increasingly ubiquitous in numerous applications and systems, necessitating explanations of their predictions, especially when making criti…

cs.LG2022

PGX: A Multi-level GNN Explanation Framework Based on Separate Knowledge Distillation Processes

Tien-Cuong Bui, Wen-syan Li, Sang-Kyun Cha

Graph Neural Networks (GNNs) are widely adopted in advanced AI systems due to their capability of representation learning on graph data. Even though GNN explanation is crucial to i…

cs.LG2019★ 3 cited

Spatiotemporal deep learning model for citywide air pollution interpolation and prediction

Van-Duc Le, Tien-Cuong Bui, Sang Kyun Cha

Recently, air pollution is one of the most concerns for big cities. Predicting air quality for any regions and at any time is a critical requirement of urban citizens. However, air…

cs.LG2018★ 59 cited

A Deep Learning Approach for Forecasting Air Pollution in South Korea Using LSTM

Tien-Cuong Bui, Van-Duc Le, Sang-Kyun Cha

Tackling air pollution is an imperative problem in South Korea, especially in urban areas, over the last few years. More specially, South Korea has joined the ranks of the world's…