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Found 7 papers, 4 papers with code
MGARD: A multigrid framework for high-performance, error-controlled data compression and refactoring
We describe MGARD, a software providing MultiGrid Adaptive Reduction for floating-point scientific data on structured and unstructured grids.
Spatiotemporally adaptive compression for scientific dataset with feature preservation -- a case study on simulation data with extreme climate events analysis
Additionally, we integrate spatiotemporal feature detection with data compression and demonstrate that performing adaptive error-bounded compression in higher dimensional space enables greater compression ratios, leveraging the error propagation theory of a transformation-based compressor.
Dissipative residual layers for unsupervised implicit parameterization of data manifolds
We parameterize such a dynamical system with a residual neural network and propose a spectral localization technique to ensure it is locally attractive in the vicinity of data.
Stable Anderson Acceleration for Deep Learning
Anderson acceleration (AA) is an extrapolation technique designed to speed-up fixed-point iterations like those arising from the iterative training of DL models.
A nonlocal feature-driven exemplar-based approach for image inpainting
We present a nonlocal variational image completion technique which admits simultaneous inpainting of multiple structures and textures in a unified framework.
Robust learning with implicit residual networks
In this effort, we propose a new deep architecture utilizing residual blocks inspired by implicit discretization schemes.
Method of Green's potentials for elliptic PDEs in domains with random apertures
Problems with topological uncertainties appear in many fields ranging from nano-device engineering to the design of bridges.
Numerical Analysis Numerical Analysis Probability 65N38, 65N80, 65N85, 65C05
