317 citations · 721 across the 36 of their papers we have counts for
4 papers · 1 filter
Physics-Informed Neural Network for Modelling the Thermochemical Curing Process of Composite-Tool Systems During Manufacture
Sina Amini Niaki, Ehsan Haghighat, Trevor Campbell +2
We present a Physics-Informed Neural Network (PINN) to simulate the thermochemical evolution of a composite material on a tool undergoing cure in an autoclave. In particular, we so…
Finite mixture models do not reliably learn the number of components
Diana Cai, Trevor Campbell, Tamara Broderick
Scientists and engineers are often interested in learning the number of subpopulations (or components) present in a data set. A common suggestion is to use a finite mixture model (…
Slice Sampling for General Completely Random Measures
Peiyuan Zhu, Alexandre Bouchard-Côté, Trevor Campbell
Completely random measures provide a principled approach to creating flexible unsupervised models, where the number of latent features is infinite and the number of features that i…
Truncated Simulation and Inference in Edge-Exchangeable Networks
Xinglong Li, Trevor Campbell
Edge-exchangeable probabilistic network models generate edges as an i.i.d.~sequence from a discrete measure, providing a simple means for statistical inference of latent network pr…