Physics-aware machine learning integrates domain-specific physical knowledge into machine learning models, leading to the development of physics-informed neural networks (PINNs). PINNs embed physical ...
Abstract: Wind-induced deflection has become a leading cause of faults in transmission lines under extreme weather conditions. This paper proposes a computational method for accurately assessing ...
Abstract: We present ComputPlasma, a Python-based plasma simulation framework developed to support research in semiconductor process modeling, particularly for plasma-assisted etching and deposition ...
This work introduces a model-agnostic framework for training and inference to enable accurate partial differential equation solving (down to double precision) for problems with arbitrary sizes and ...
This repo contains the JAX implementation of our ICLR 2024 paper, Neural Spectral Methods: Self-supervised learning in the spectral domain. Yiheng Du, Nithin ...
It provides reliable algorithms for handling non-linear constraints. In particular, roundoff errors are also taken into account. It is based on interval arithmetic. The main feature of Ibex is its ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. An easy-to-implement noise estimation method for tuning state estimators is proposed.
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Article Views are the COUNTER-compliant sum of full text article downloads since ...
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