12 citations · 20 across the 4 of their papers we have counts for
4 papers
Physics-Informed Gaussian Process Inference of Liquid Structure from Scattering Data
Harry W. Sullivan, Brennon L. Shanks, Matej Cervenka +1
We present a nonparametric Bayesian framework to infer radial distribution functions from experimental scattering measurements with uncertainty quantification using non-stationary…
Experimental Evidence of Quantum Drude Oscillator Behavior in Liquids Revealed with Probabilistic Iterative Boltzmann Inversion
Brennon L. Shanks, Harry W. Sullivan, Pavel Jungwirth +1
The first experimental evidence of quantum Drude oscillator behavior in liquids is determined using probabilistic machine learning-augmented iterative Boltzmann inversion applied t…
Bayesian Analysis Reveals the Key to Extracting Pair Potentials from Neutron Scattering Data
Brennon L. Shanks, Harry W. Sullivan, Michael P. Hoepfner
The inverse problem of statistical mechanics is an unsolved, century-old challenge to learn classical pair potentials directly from experimental scattering data. This problem was e…
Accelerated Bayesian Inference for Molecular Simulations using Local Gaussian Process Surrogate Models
B. L. Shanks, H. W. Sullivan, A. R. Shazed +1
While Bayesian inference is the gold standard for uncertainty quantification and propagation, its use within physical chemistry encounters formidable computational barriers. These…