Zobrazeno 1 - 10
of 24 418
pro vyhledávání: '"Humer"'
In computational engineering, enhancing the simulation speed and efficiency is a perpetual goal. To fully take advantage of neural network techniques and hardware, we present the SLiding-window Initially-truncated Dynamic-response Estimator (SLIDE),
Externí odkaz:
http://arxiv.org/abs/2409.18272
Autor:
Vu-Quoc, Loc, Humer, Alexander
Publikováno v:
International Journal for Numerical Methods in Engineering, 2024;e7586
Several forms for constructing novel physics-informed neural-networks (PINN) for the solution of partial-differential-algebraic equations based on derivative operator splitting are proposed, using the nonlinear Kirchhoff rod as a prototype for demons
Externí odkaz:
http://arxiv.org/abs/2408.01914
Diffusion models generate high-quality samples by corrupting data with Gaussian noise and iteratively reconstructing it with deep learning, slowly transforming noisy images into refined outputs. Understanding this data evolution is important for inte
Externí odkaz:
http://arxiv.org/abs/2406.17462
Magnonics is an emerging research field that addresses the use of spin waves (magnons), purely magnetic waves, for information transport and processing. Spin waves are a potential replacement for electric current in modern computational devices that
Externí odkaz:
http://arxiv.org/abs/2405.03506
We report modifications of the ph-AFQMC algorithm that allow the use of large time steps and reliable time step extrapolation. Our modified algorithm eliminates size-consistency errors present in the standard algorithm when large time steps are emplo
Externí odkaz:
http://arxiv.org/abs/2403.02542
