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Deep Autoencoder

model1 events
papersTODAY 04:00 UTC

Deep Autoencoder Estimates Intrinsic Dimensionality of FPUT Trajectories

The paper applies a deep autoencoder to estimate the intrinsic dimensionality of high-dimensional trajectories from the Fermi-Pasta-Ulam-Tsingou beta model with 32 oscillators. The dataset spans roughly 4 million data points, and the authors take a nonlinear approach to characterize the underlying low-dimensional structure of the dynamics.

autoencoders/physics/dimensionality-reduction/research