Detection and skeletonization of single neurons and tracer injections using topological methods

no code implementations • 20 Mar 2020 • Dingkang Wang, Lucas Magee, Bing-Xing Huo, Samik Banerjee, Xu Li, Jaikishan Jayakumar, Meng Kuan Lin, Keerthi Ram, Suyi Wang, Yusu Wang, Partha P. Mitra

Neuroscientific data analysis has traditionally relied on linear algebra and stochastic process theory.

Equivariant geometric learning for digital rock physics: estimating formation factor and effective permeability tensors from Morse graph

no code implementations • 12 Apr 2021 • Chen Cai, Nikolaos Vlassis, Lucas Magee, Ran Ma, Zeyu Xiong, Bahador Bahmani, Teng-Fong Wong, Yusu Wang, WaiChing Sun

Comparisons among predictions inferred from training the CNN and those from graph convolutional neural networks (GNN) with and without the equivariant constraint indicate that the equivariant graph neural network seems to perform better than the CNN and GNN without enforcing equivariant constraints.