Junqi Yin Computational Scientist Contact 865.241.8099 | YINJ@ORNL.GOV All Publications Towards the holistic design of alloys with large language models Designing complex concentrated alloys with quantum machine learning and language modeling Comparative Study of Large Language Model Architectures on Frontier... FORGE: Pre-Training Open Foundation Models for Science Evaluation of pre-training large language models on leadership-class supercomputers DeepThermo: Deep Learning Accelerated Parallel Monte Carlo Sampling for Thermodynamics Evaluation of High Entropy Alloys A scalable transformer model for real-time decision making in neutron scattering experiments Toward the design of ultrahigh-entropy alloys via mining six million texts... Strategies for Integrating Deep Learning Surrogate Models with HPC Simulation Applications Accelerating Collective Communication in Data Parallel Training across Deep Learning Frameworks Comparative evaluation of deep learning workloads for leadership-class systems Neural network-based order parameter for phase transitions and its applications in high-entropy alloys chatHPC: Empowering HPC users with large language models Integrated edge-to-exascale workflow for real-time steering in neutron scattering experiments A Scalable Real-Time Data Assimilation Framework for Predicting Turbulent Atmosphere Dynamics ORBIT: Oak Ridge Base Foundation Model for Earth System Predictability... Enabling Low-Overhead HT-HPC Workflows at Extreme Scale using GNU Parallel The Case for Co-Designing Model Architectures with Hardware First-principles data for solid solution niobium-tantalum-vanadium alloys with body-centered-cubic structures Roadmap on data-centric materials science Optimizing Distributed Training on Frontier for Large Language Models Pretraining Billion-Scale Geospatial Foundational Models on Frontier Evaluating the Cloud for Capability Class Leadership Workloads... Toward an Autonomous Workflow for Single Crystal Neutron Diffraction Machine Learning for First Principles Calculations of Material Properties for Ferromagnetic Materials Pagination Current page 1 Page 2 Page 3 Next page ›â¶Äº Last page Last » Key Links Organizations Computing and Computational Sciences Directorate National Center for Computational Sciences Advanced Technologies Section Analytics and AI Methods at Scale Group
