activity
20162023
most citedVortex arrays and ciliary tangles underlie the feeding-swimming tradeoff in starfish larvae

114 citations · 251 across the 9 of their papers we have counts for

collaborators

9 papers

cs.LG2023★ 1 cited

Model scale versus domain knowledge in statistical forecasting of chaotic systems

William Gilpin

Chaos and unpredictability are traditionally synonymous, yet large-scale machine learning methods recently have demonstrated a surprising ability to forecast chaotic systems well b…

cond-mat.soft2022★ 2 cited

Curiosity-driven search for novel non-equilibrium behaviors

Martin J. Falk, Finnegan D. Roach, William Gilpin +1

Exploring the spectrum of novel behaviors a physical system can produce can be a labor-intensive task. Active learning is a collection of iterative sampling techniques developed in…

cs.LG2021★ 4 cited

Chaos as an interpretable benchmark for forecasting and data-driven modelling

William Gilpin

The striking fractal geometry of strange attractors underscores the generative nature of chaos: like probability distributions, chaotic systems can be repeatedly measured to produc…

cs.LG2020★ 35 cited

Deep reconstruction of strange attractors from time series

William Gilpin

Experimental measurements of physical systems often have a limited number of independent channels, causing essential dynamical variables to remain unobserved. However, many popular…

physics.flu-dyn2019

Lagrange2D: A Mathematica package for Lagrangian analysis of two-dimensional fluid flows

William Gilpin

We introduce Lagrange2D, a Mathematica package for analysis and characterization of complex fluid flows using Lagrangian transport metrics. Lagrange2D includes built-in functions f…

nlin.AO2019★ 4 cited

Avalanches impede synchronization of jammed oscillators

William Gilpin

Synchrony is inevitable in many oscillating systems -- from the canonical alignment of two ticking grandfather clocks, to the mutual entrainment of beating flagella or spiking neur…

nlin.CG2018★ 90 cited

Cellular automata as convolutional neural networks

William Gilpin

Deep learning techniques have recently demonstrated broad success in predicting complex dynamical systems ranging from turbulence to human speech, motivating broader questions abou…

physics.flu-dyn2018★ 1 cited

Rapid behavioral transitions produce chaotic mixing by a planktonic microswimmer

William Gilpin, Vivek N. Prakash, Manu Prakash

Despite their vast morphological diversity, many invertebrates have similar larval forms characterized by ciliary bands, innervated arrays of beating cilia that facilitate swimming…

physics.flu-dyn2016★ 114 cited

Vortex arrays and ciliary tangles underlie the feeding-swimming tradeoff in starfish larvae

William Gilpin, Vivek N. Prakash, Manu Prakash

Many marine invertebrates have larval stages covered in linear arrays of beating cilia, which propel the animal while simultaneously entraining planktonic prey. These bands are str…