3 citations · 5 across the 3 of their papers we have counts for
3 papers
q-bio.QM2026
Diffusion learning reveals viable parameter manifolds and compensation geometry in biological dynamical systems
Ruilin Zhang, Louis Tao, Zhuo-Cheng Xiao
Models of complex systems often have many parameters, yet are constrained by far fewer experimentally accessible observables; consequently, similar activity can emerge from coordin…
nlin.AO2022★ 3 cited
Learning biological neuronal networks with artificial neural networks: neural oscillations
Ruilin Zhang, Zhongyi Wang, Tianyi Wu +4
First-principles-based modelings have been extremely successful in providing crucial insights and predictions for complex biological functions and phenomena. However, they can be h…
q-bio.NC2022★ 2 cited
Multi-band oscillations emerge from a simple spiking network
Tianyi Wu, Yuhang Cai, Ruilin Zhang +3
In the brain, coherent neuronal activities often appear simultaneously in multiple frequency bands, e.g., as combinations of alpha (8-12 Hz), beta (12.5-30 Hz), gamma (30-120 Hz) o…