52 citations · 180 across the 17 of their papers we have counts for
17 papers
Multistable energy landscapes for adaptive microscopic machines
Melody Xuan Lim, Zexi Liang, Gabriel Alkuino +5
The past few years have seen great strides in our ability to build synthetic microscopic machines. However, the function of such machines is often controlled directly by externally…
An Analytical Characterization of Sloppiness in Neural Networks: Insights from Linear Models
Jialin Mao, Itay Griniasty, Yan Sun +3
Recent experiments have shown that training trajectories of multiple deep neural networks with different architectures, optimization algorithms, hyper-parameter settings, and regul…
Programming evolution of geometry in shape-morphing sheets via spatiotemporal activation
Daniel Duffy, Itay Griniasty, John Biggins +1
Shape-programmed sheets morph from one surface into another upon activation by stimuli such as illumination, and have attracted much interest for their potential engineering applic…
The Training Process of Many Deep Networks Explores the Same Low-Dimensional Manifold
Jialin Mao, Itay Griniasty, Han Kheng Teoh +5
We develop information-geometric techniques to analyze the trajectories of the predictions of deep networks during training. By examining the underlying high-dimensional probabilis…
Bifurcation instructed design of multistate machines
Teaya Yang, David Hathcock, Yuchao Chen +4
We propose a novel design paradigm for multistate machines where transitions from one state to another are organized by bifurcations of multiple equilibria of the energy landscape…
Discontinuous metric programming in liquid crystalline elastomers
Tayler S. Hebner, Riley G. A. Bowman, Daniel Duffy +6
Liquid crystalline elastomers (LCEs) are shape-changing materials that exhibit large deformations in response to applied stimuli. Local control of the orientation of LCEs spatially…