Harnessing Machine Learning to Understand and Design Disordered Solids
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source
A note on the analysis of Herrmann-May lattices for small exponent RSA. [PDF]
Kalam A, Karmakar S, Sarkar S.
europepmc +1 more source
An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting
Architecture of the proposed large language model (LLM)‐based agent framework for autonomous time series forecasting in thermal power generation systems. The framework operates through a vertical pipeline initiated by natural language queries from users, which are processed by the LLM Agent Core powered by Llama.cpp and a ReAct loop with persistent ...
William Gouvêa Buratto +5 more
wiley +1 more source
Jacobi-Ritz formulation for modal analysis of thick, anisotropic and non-uniform electric motor stator assemblies considering axisymmetric vibration modes. [PDF]
Andreou P +3 more
europepmc +1 more source
A machine learning framework simultaneously predicts four critical properties of monomers for emulsion polymerization: propagation rate constant, reactivity ratios, glass transition temperature, and water solubility. These tools can be used to systematically identify viable bio‐based monomer pairs as replacements for conventional formulations, with ...
Kiarash Farajzadehahary +1 more
wiley +1 more source
Analysis of RL electric circuits modeled by fractional Riccati IVP via Jacobi-Broyden Newton algorithm. [PDF]
Abd El-Hady M +3 more
europepmc +1 more source
On the best polynomial approximation of analytical functions in the Bergman space B2
М. Ш. Шабозов +1 more
openalex +1 more source
On nonparametric estimating ROC curve based on non-uniform rational B-spline. [PDF]
Erdoğan MS.
europepmc +1 more source
Quantum speedup for nonreversible Markov chains. [PDF]
Claudon B, Piquemal JP, Monmarché P.
europepmc +1 more source
3D dendritic spines shape descriptors for efficient classification and morphology analysis in control and Alzheimer's disease modeling neurons. [PDF]
Smirnova D +3 more
europepmc +1 more source

