MLIP Studio unifies 60+ universal machine learning interatomic potentials in a free web platform for interactive atomistic simulations, benchmarking, and MLIP-accelerated DFT workflows.
Mlipaudit: A benchmarking tool for machine learned interatomic potentials
3 Pith papers cite this work, alongside 1 external citations. Polarity classification is still indexing.
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2026 3representative citing papers
Benchmarks of 15 MLIPs show parameter count and training set size correlate with accuracy, architecture drives speed and memory, and explicit Coulomb terms provide no benefit.
mlip v2 is a new software release that integrates API redesign, e3j backend, eSEN model, improved charge modeling, and expanded simulation capabilities to support larger-scale molecular modeling.
citing papers explorer
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MLIP Studio: An Open Platform for Interactive Benchmarking and Atomistic Simulations Using Machine Learning Interatomic Potentials
MLIP Studio unifies 60+ universal machine learning interatomic potentials in a free web platform for interactive atomistic simulations, benchmarking, and MLIP-accelerated DFT workflows.
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Accuracy and Efficiency Benchmarks of Pretrained Machine Learning Potentials for Molecular Simulations
Benchmarks of 15 MLIPs show parameter count and training set size correlate with accuracy, architecture drives speed and memory, and explicit Coulomb terms provide no benefit.
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Machine Learning Interatomic Potentials: Advancing Open-Source Software for Efficient and Scalable Molecular Simulation
mlip v2 is a new software release that integrates API redesign, e3j backend, eSEN model, improved charge modeling, and expanded simulation capabilities to support larger-scale molecular modeling.