Results 51 to 60 of about 28,484 (217)
Advanced Intelligent Discovery, EarlyView.Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee +3 more
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Advanced Intelligent Discovery, EarlyView.In this work, the Doubao large language model (LLM) is involved in the formula derivation processes for Hubbard U determination regarding the second‐order perturbations of the chemical potential. The core ML tool is optimized for physical domain knowledge, which is not limited to parameter prediction but rather serves as an interactive physical theory ...
Mingzi Sun +8 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.This study reveals that sampling strategy (i.e., sampling size and approach) is a foundational prerequisite for building accurate and generalizable AI models in peptide discovery. Reaching a threshold of 7.5% of the total tetrapeptide sequence space was essential to ensure reliable predictions.
Meiru Yan +3 more
wiley +1 more source
An approximation theorem and generic convergence for equilibrium problems. [PDF]
J Inequal Appl, 2018 Qiu X, Jia W, Peng D.
europepmc +1 more source
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.This review aims to provide a broad understanding for interdisciplinary researchers in engineering and clinical applications. It addresses the development and control of magnetic actuation systems (MASs) in clinical surgeries and their revolutionary effects in multiple clinical applications.
Yingxin Huo +3 more
wiley +1 more source
A Fix-Finite Approximation Theorem
Rocky Mountain Journal of Mathematics, 2004 Let \(E\) be a metrizable locally convex vector space whose topology is defined by a translation invariant metric \(d\) given by \(d(x,y)=\sum^\infty_{h=1}\frac1{2^n}\;\frac{p_n(x-y)}{1+p_n(x-y)}\).Let \(C(E)\) be the set of non-empty compact subsets of \(E\). For \(A,B\in C(E)\), the Hausdorff distance is defined as \(d_H(A,B)=\max\{P(A,B),P(B,A)\}\),
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Predicting Performance of Hall Effect Ion Source Using Machine Learning
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park +8 more
wiley +1 more source
Topological Minimax Theorems and Approximation
Journal of Mathematical Analysis and Applications, 1997 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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