Seung-Hwan Lim Research Scientist Contact LIMS1@ORNL.GOV All Publications SNNVis: Visualizing Graph Embedding of Evolutionary Optimization for Spiking Neural Networks Scaling neural simulations in STACS Explaining Neural Spike Activity for Simulated Bio-plausible Network through Deep Sequence Learning Efficient graph representation framework for chemical molecule similarity tasks Hyperparameter Optimization and Feature Inclusion in Graph Neural Networks for Spiking Implementation Attention for Causal Relationship Discovery from Biological Neural Dynamics... Knowledge-Informed Uncertainty-Aware Machine Learning for Time Series Forecasting of Dynamical Engineered Systems UnifyFS: A User-level Shared File System for Unified Access to Distributed Local Storage... Neuromorphic Computing for Scientific Applications Augmenting Graph Convolution with Distance Preserving Embedding for Improved Learning... Exaflops Biomedical Knowledge Graph Analytics Semi-Supervised Graph Structure Learning on Neuromorphic Computers Smoky Mountain Data Challenge 2021: An Open Call to Solve Scientific Data Challenges Using Advanced Data Analytics and Edge Computing Community Fabric: Visualizing Communities and Structure in Dynamic Networks Performance Profile of Transformer Fine-Tuning in Multi-GPU Cloud Environments Visual Understanding of COVID-19 Knowledge Graph for Predictive Analysis Versatile feature learning with graph convolutions and graph structures Revisit the Scalability of Deep Auto-Regressive Models for Graph Generation An Integrated Indexing and Search Service for Distributed File Systems Toward Large-Scale Image Segmentation on Summit Understanding the Interplay between Hardware Errors and User Job Characteristics on the Titan Supercomputer MARBLE: A Multi-GPU Aware Job Scheduler for Deep Learning on HPC Systems FLEET: Flexible Efficient Ensemble Training for Heterogeneous Deep Neural Networks Exascale Deep Learning to Accelerate Cancer Research In-Place Zero-Space Memory Protection for CNN Pagination Current page 1 Page 2 Page 3 Next page ›› Last page Last » Key Links ORCID Organizations Computing and Computational Sciences Directorate Computer Science and Mathematics Division Mathematics in Computation Section Discrete Algorithms Group
Research Highlight Adaptive Single Parameter Total Variation Regularization for Derivative Estimation
