Kernels from pretrained MLIP latent spaces outperform standard acquisition methods in active learning for reactive chemistry, reducing required labels by 38% for energy error and 28% for force error.
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Improved tangent estimate in the nudged elastic band method for finding minimum energy paths and saddle points.The Journal of Chemical Physics, 113(22):9978–9985, 12 2000
9 Pith papers cite this work, alongside 8,806 external citations. Polarity classification is still indexing.
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cond-mat.mtrl-sci 2 cs.LG 2 math.NA 1 physics.bio-ph 1 physics.chem-ph 1 quant-ph 1 stat.ML 1years
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NEB-adapted ravine ensembles for QNNs classifying concentratable entanglement outperform naive methods when local-prediction variability is high and reduce costs, with ravines persisting under depth and qubit scaling.
Develops a Laguerre spectral minimum action method with time rescaling and improved quadrature for efficient quasi-potential computation in infinite-horizon problems.
Anharmonic calculations show random CoCrNi ISFE decreases and stays negative with temperature while LCO ISFE stays positive from 0-1000 K, with MD confirming unbounded vs finite dislocation dissociation.
Force-aware Neural Tangent Kernels combined with chunked acquisition provide scalable and distribution-robust active learning for MLIPs, outperforming baselines on OC20 and remaining competitive on other benchmarks.
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.
NO2 adsorption on alpha-Fe2O3 transfers 0.72 electrons and quenches surface small polarons, suppressing polaronic conductivity and explaining sensor resistance increase.
Bayesian optimization with Gaussian processes unifies minimization, single-point saddle searches, and double-ended path searches on potential energy surfaces through a shared six-step surrogate loop using derivative observations and inverse-distance kernels.
QM/MM simulations find that Glu-to-Asp mutation raises the catalytic barrier in CviUPO while Cys-to-His lowers it but may shift the enzyme toward peroxidase behavior.
citing papers explorer
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Pretrained Model Representations as Acquisition Signals for Active Learning of MLIPs
Kernels from pretrained MLIP latent spaces outperform standard acquisition methods in active learning for reactive chemistry, reducing required labels by 38% for energy error and 28% for force error.
-
Ravines in quantum cost landscapes: opportunities for improved VQA predictions
NEB-adapted ravine ensembles for QNNs classifying concentratable entanglement outperform naive methods when local-prediction variability is high and reduce costs, with ravines persisting under depth and qubit scaling.
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An Efficient Laguerre Minimum Action Method for Computing Quasi-Potentials
Develops a Laguerre spectral minimum action method with time rescaling and improved quadrature for efficient quasi-potential computation in infinite-horizon problems.
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Finite Temperature Stacking Fault Stability in Random and Locally Ordered CoCrNi beyond the Harmonic Approximation
Anharmonic calculations show random CoCrNi ISFE decreases and stays negative with temperature while LCO ISFE stays positive from 0-1000 K, with MD confirming unbounded vs finite dislocation dissociation.
-
Force-Aware Neural Tangent Kernels for Scalable and Robust Active Learning of MLIPs
Force-aware Neural Tangent Kernels combined with chunked acquisition provide scalable and distribution-robust active learning for MLIPs, outperforming baselines on OC20 and remaining competitive on other benchmarks.
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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.
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Polaron Conductivity in $\alpha$-Fe2O3 Quenched by Adsorbed NO2
NO2 adsorption on alpha-Fe2O3 transfers 0.72 electrons and quenches surface small polarons, suppressing polaronic conductivity and explaining sensor resistance increase.
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A Tutorial Review of Bayesian Optimization with Gaussian Processes to Accelerate Stationary Point Searches
Bayesian optimization with Gaussian processes unifies minimization, single-point saddle searches, and double-ended path searches on potential energy surfaces through a shared six-step surrogate loop using derivative observations and inverse-distance kernels.
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Computationally guided modifications of CviUPO to improve catalytic activity
QM/MM simulations find that Glu-to-Asp mutation raises the catalytic barrier in CviUPO while Cys-to-His lowers it but may shift the enzyme toward peroxidase behavior.