University of Washington Applied Physics Laboratory

CS-SHRED: enhancing SHRED for robust recovery of spatiotemporal dynamics

Abstract We present CS-SHRED, a novel deep learning architecture that integrates compressed sensing (CS) into a shallow recurrent decoder (SHRED) to reconstruct spatiotemporal dynamics from incomplete, compressed or corrupted data. Our approach introduces two key innovations. Fir...

Viscoelastic Response of Crosslinked Rubber: Coarse‐Grained Molecular Dynamics and Time‐Temperature Superposition

ABSTRACT The viscoelastic response of crosslinked rubber was investigated using coarse‐grained molecular dynamics simulations combined with time‐temperature superposition. Crosslinked polymer networks containing different numbers of crosslinkers were generated using a dynamic rea...

Subspace Langevin Monte Carlo

Abstract. Sampling from high-dimensional distributions has wide applications in data science and machine learning but poses significant computational challenges. We introduce subspace Langevin Monte Carlo (SLMC), a novel and efficient sampling method that generalizes random-coord...

Sustainable Metal–Organic Framework Water Harvesters in the Artificial Intelligence Era

Abstract Metal–organic frameworks (MOFs) are promising candidates for water harvesting due to their tunable pore environments, which can be precisely engineered to capture and release water in arid conditions. Integrating artificial intelligence (AI) into MOF discovery can accele...

Measuring Ocean Surface Waves

Abstract Propagating waves on the ocean surface can be represented as a stochastic process whose statistics are characterized by a spectrum. This paper reviews methods for measuring the wave spectrum and related quantities. Observations begin by sensing fluid dynamical properties...

Buffon discrepancy and the Steinhaus longimeter

Abstract Let be a convex set. We study the problem of distributing a one‐dimensional set with total length so that for any line in the number of intersections is proportional to the length as much as possible; we use the term Buffon discrepancy for the largest error. A constructi...