3 citations · 7 across the 3 of their papers we have counts for
6 papers
Spacetime Autoencoders Using Local Causal States
Adam Rupe, James P. Crutchfield
Local causal states are latent representations that capture organized pattern and structure in complex spatiotemporal systems. We expand their functionality, framing them as spacet…
DisCo: Physics-Based Unsupervised Discovery of Coherent Structures in Spatiotemporal Systems
Adam Rupe, Nalini Kumar, Vladislav Epifanov +8
Extracting actionable insight from complex unlabeled scientific data is an open challenge and key to unlocking data-driven discovery in science. Complementary and alternative to su…
Towards Unsupervised Segmentation of Extreme Weather Events
Adam Rupe, Karthik Kashinath, Nalini Kumar +3
Extreme weather is one of the main mechanisms through which climate change will directly impact human society. Coping with such change as a global community requires markedly impro…
Koopman Operator and its Approximations for Systems with Symmetries
Anastasiya Salova, Jeffrey Emenheiser, Adam Rupe +2
Nonlinear dynamical systems with symmetries exhibit a rich variety of behaviors, including complex attractor-basin portraits and enhanced and suppressed bifurcations. Symmetry argu…
Spacetime Symmetries, Invariant Sets, and Additive Subdynamics of Cellular Automata
Adam Rupe, James P. Crutchfield
Cellular automata are fully-discrete, spatially-extended dynamical systems that evolve by simultaneously applying a local update function. Despite their simplicity, the induced glo…
A Physics-Based Approach to Unsupervised Discovery of Coherent Structures in Spatiotemporal Systems
A. Rupe, J. P. Crutchfield, K. Kashinath +1
Given that observational and numerical climate data are being produced at ever more prodigious rates, increasingly sophisticated and automated analysis techniques have become essen…