2 citations · 4 across the 3 of their papers we have counts for
5 papers
Self-organization of multi-layer spiking neural networks
Guruprasad Raghavan, Cong Lin, Matt Thomson
Living neural networks in our brains autonomously self-organize into large, complex architectures during early development to result in an organized and functional organic computat…
Geometric algorithms for predicting resilience and recovering damage in neural networks
Guruprasad Raghavan, Jiayi Li, Matt Thomson
Biological neural networks have evolved to maintain performance despite significant circuit damage. To survive damage, biological network architectures have both intrinsic resilien…
Neural networks grown and self-organized by noise
Guruprasad Raghavan, Matt Thomson
Living neural networks emerge through a process of growth and self-organization that begins with a single cell and results in a brain, an organized and functional computational dev…
Active Learning of Spin Network Models
Jialong Jiang, David A. Sivak, Matt Thomson
The inverse statistical problem of finding direct interactions in complex networks is difficult. In the natural sciences, well-controlled perturbation experiments are widely used t…
Controlling Organization and Forces in Active Matter Through Optically-Defined Boundaries
Tyler D. Ross, Heun Jin Lee, Zijie Qu +3
Living systems are capable of locomotion, reconfiguration, and replication. To perform these tasks, cells spatiotemporally coordinate the interactions of force-generating, "active"…