68 citations · 110 across the 9 of their papers we have counts for
4 papers · 1 filter
Generating Physically Sound Designs from Text and a Set of Physical Constraints
Gregory Barber, Todd C. Henry, Mulugeta A. Haile
We present TIDES, a text informed design approach for generating physically sound designs based on a textual description and a set of physical constraints. TIDES jointly optimizes…
Physical Constraint Embedded Neural Networks for inference and noise regulation
Gregory Barber, Mulugeta A. Haile, Tzikang Chen
Neural networks often require large amounts of data to generalize and can be ill-suited for modeling small and noisy experimental datasets. Standard network architectures trained o…
Joint Parameter Discovery and Generative Modeling of Dynamic Systems
Gregory Barber, Mulugeta A. Haile, Tzikang Chen
Given an unknown dynamic system such as a coupled harmonic oscillator with springs and point masses. We are often interested in gaining insights into its physical parameters, i…
Adaptable Hamiltonian neural networks
Chen-Di Han, Bryan Glaz, Mulugeta Haile +1
The rapid growth of research in exploiting machine learning to predict chaotic systems has revived a recent interest in Hamiltonian Neural Networks (HNNs) with physical constraints…