Smith, Justin S.

1. Multi-fidelity learning for interatomic potentials: Low-level forces and high-level energies are all you need
   2025/05/02 by Sakib Matin, Messerly, Mitchell, Alice E. A. Allen +12 · 6 citations
   Materials Science · #Chemical Physics (physics.chem-ph) #Computational Physics (physics.comp-ph) #FOS: Physical sciences #Machine Learning in Materials Science
2. Machine learning potentials with Iterative Boltzmann Inversion: training to experiment
   2023/07/10 by Sakib Matin, Alice Allen, Matin, Sakib +17 · 2 citations
   Biochemistry, Genetics and Molecular Biology · Materials Science · Physics and Astronomy · #Applied Physics (physics.app-ph) #FOS: Physical sciences #Machine Learning in Materials Science #Model Reduction and Neural Networks #Protein Structure and Dynamics
3. Closed-Loop Benchmarking of Stereo Visual-Inertial SLAM Systems: Understanding the Impact of Drift and Latency on Tracking Accuracy
   2020/03/03 by Yipu Zhao, Justin S. Smith, Zhao, Yipu +5 · 1 citation
   Engineering · #Robotics and Sensor-Based Localization #Underwater Vehicles and Communication Systems #Indoor and Outdoor Localization Technologies
4. Simple and efficient algorithms for training machine learning potentials to force data
   2020/06/09 by Justin S. Smith, Nicholas Lubbers, Smith, Justin S. +5 · 1 citation
   Chemistry · Computer Science · Materials Science · #Computational Drug Discovery Methods #Computational Physics (physics.comp-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (stat.ML) #Machine Learning in Materials Science #Materials Science (cond-mat.mtrl-sci) #Various Chemistry Research Topics
5. Quantum-based Molecular Dynamics Simulations Using Tensor Cores
   2021/07/06 by Finkelstein, Joshua, Smith, Justin S., Mniszewski, Susan M. +4 · 1 citation
   #Computational Physics (physics.comp-ph) #FOS: Physical sciences #Quantum Physics (quant-ph)
6. Good Graph to Optimize: Cost-Effective, Budget-Aware Bundle Adjustment in Visual SLAM
   2020/08/23 by Zhao, Yipu, Smith, Justin S., Vela, Patricio A. · 1 citation
   #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Robotics (cs.RO)
7. Optimizing Data Distribution and Kernel Performance for Efficient Training of Chemistry Foundation Models: A Case Study with MACE
   2025/04/14 by Jesun Firoz, Franco Pellegrini, Firoz, Jesun +35 · 2 citations
   Computer Science · Materials Science · #Advanced Graph Neural Networks #Artificial Intelligence (cs.AI) #Distributed #FOS: Computer and information sciences #Graph Theory and Algorithms #Machine Learning in Materials Science #Parallel #and Cluster Computing (cs.DC)