Results 1 to 10 of about 2,379,681 (212)
RANG: A Residual-based Adaptive Node Generation Method for Physics-Informed Neural Networks [PDF]
arXiv.org, 2022 Learning solutions of partial differential equations (PDEs) with Physics-Informed Neural Networks (PINNs) is an attractive alternative approach to traditional solvers due to its flexibility and ease of incorporating observed data.
Wei Peng +4 more
openalex +3 more sources
Graph coloring with physics-inspired graph neural networks [PDF]
Physical Review Research, 2022 We show how graph neural networks can be used to solve the canonical graph coloring problem. We frame graph coloring as a multiclass node classification problem and utilize an unsupervised training strategy based on the statistical physics Potts model ...
Martin J. A. Schuetz +3 more
doaj +2 more sources
Reconstruction Thresholds on Regular Trees [PDF]
Discrete Mathematics & Theoretical Computer Science, 2003 We consider themodel of broadcasting on a tree, with binary state space, on theinfinite rooted tree $T^k$ in which each node has $k$ children. The root of the tree takesa random value $0$ or $1$, and then each node passes a value independently to each of
James B. Martin
doaj +5 more sources
CaTe: a new topological node-line and Dirac semimetal [PDF]
npj Quantum Materials, 2017 Topological physics: a predicted node-line semimetal CaTe Topological insulators are materials with non-trivial topological order that are insulating in their bulk but conductive on their surface.
Yongping Du +7 more
doaj +2 more sources
MBD-NODE: Physics-informed data-driven modeling and simulation of constrained multibody systems [PDF]
Multibody system dynamicsJingquan Wang +4 more
semanticscholar +3 more sources
IEEE Journal of the Electron Devices Society, 2018 We present a comprehensive theoretical investigation of the quantum confinement limited mobility in the Si1-xGex-channel gate-all-around nanosheet field effect transistor for 5-nm node.
Jiaxin Yao +10 more
doaj +2 more sources
Network Representation Learning: From Preprocessing, Feature Extraction to Node Embedding [PDF]
ACM Computing Surveys, 2021 Network representation learning (NRL) advances the conventional graph mining of social networks, knowledge graphs, and complex biomedical and physics information networks. Dozens of NRL algorithms have been reported in the literature.
Jingya Zhou +3 more
semanticscholar +1 more source
Unifying over-smoothing and over-squashing in graph neural networks: A physics informed approach and beyond [PDF]
arXiv.org, 2023 Graph Neural Networks (GNNs) have emerged as one of the leading approaches for machine learning on graph-structured data. Despite their great success, critical computational challenges such as over-smoothing, over-squashing, and limited expressive power ...
Zhiqi Shao +5 more
semanticscholar +1 more source
Fractal and Fractional, 2023 In this research work, we investigate the complex structure of soliton in the Fractional Kudryashov–Sinelshchikov Equation (FKSE) using conformable fractional derivatives.
Rashid Ali +5 more
doaj +1 more source
Benchmarks for physics-informed data-driven hyperelasticity [PDF]
arXiv.org, 2023 Data-driven methods have changed the way we understand and model materials. However, while providing unmatched flexibility, these methods have limitations such as reduced capacity to extrapolate, overfitting, and violation of physics constraints.
Vahidullah Tac +4 more
semanticscholar +1 more source