181 citations · 188 across the 4 of their papers we have counts for
5 papers
Efficient hyperparameter optimization by way of PAC-Bayes bound minimization
John J. Cherian, Andrew G. Taube, Robert T. McGibbon +6
Identifying optimal values for a high-dimensional set of hyperparameters is a problem that has received growing attention given its importance to large-scale machine learning appli…
Personalized Radiotherapy Design for Glioblastoma: Integrating Mathematical Tumor Models, Multimodal Scans and Bayesian Inference
Jana Lipkova, Panagiotis Angelikopoulos, Stephen Wu +11
Glioblastoma is a highly invasive brain tumor, whose cells infiltrate surrounding normal brain tissue beyond the lesion outlines visible in the current medical scans. These infiltr…
Experimental data over quantum mechanics simulations for inferring the repulsive exponent of the Lennard-Jones potential in Molecular Dynamics
Lina Kulakova, Georgios Arampatzis, Panagiotis Angelikopoulos +3
The Lennard-Jones (LJ) potential is a cornerstone of Molecular Dynamics (MD) simulations and among the most widely used computational kernels in science. The potential models atomi…
Hierarchical Stochastic Model in Bayesian Inference: Theoretical Implications and Efficient Approximation
Stephen Wu, Panagiotis Angelikopoulos, James L. Beck +1
We classify two types of Hierarchical Bayesian Model found in the literature as Hierarchical Prior Model (HPM) and Hierarchical Stochastic Model (HSM). Then, we focus on studying t…
Langevin Diffusion for Population Based Sampling with an Application in Bayesian Inference for Pharmacodynamics
Georgios Arampatzis, Daniel Wälchli, Panagiotis Angelikopoulos +3
We propose an algorithm for the efficient and robust sampling of the posterior probability distribution in Bayesian inference problems. The algorithm combines the local search capa…