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Seung-Hwan Lim

Seung-Hwan Lim

Research Scientist

Contact

LIMS1@ORNL.GOV

Bio

I am a computer scientist who works on machine learning on discrete structures like graph and sequences. 

Google scholar entry: Seung-Hwan Lim

Publications

December 2021

Versatile feature learning with graph convolutions and graph structures

Conference Paper
December 2021

Performance Profile of Transformer Fine-Tuning in Multi-GPU Cloud Environments

Conference Paper
December 2021

Visual Understanding of COVID-19 Knowledge Graph for Predictive Analysis

Conference Paper
July 2021

Revisit the Scalability of Deep Auto-Regressive Models for Graph Generation

Conference Paper
October 2020

An Integrated Indexing and Search Service for Distributed File Systems

Journal: IEEE Transactions on Parallel and Distributed Systems

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Organizations

Computing and Computational Sciences Directorate
Computer Science and Mathematics Division
Mathematics in Computation Section
Discrete Algorithms Group

Related News

Research Highlight

Translational symmetries constrain how phonons interact in layered magnets

Research Highlight

Adaptive Single Parameter Total Variation Regularization for Derivative Estimation

Research Highlight

Versatile Feature Learning with Graph Convolutions and Graph Structures

News

ORNL technologies receive six R&D 100 Awards
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