Results 61 to 70 of about 32,351,759 (213)

Formal Verification of Multi-Thread Minimax Behavior Using mCRL2 in the Connect 4

open access: yesMathematics
This study focuses on the formal verification of a parallel version of the minimax algorithm using the mCRL2 modeling language, applied to the game of Connect 4.
Diego Escobar, Jesus Insuasti
doaj   +1 more source

Ellipsoid Method for Linear Regression Parameters Determination

open access: yesКібернетика та комп'ютерні технології, 2020
Introduction. Linear regression parameters determination can be formulated as a non-smooth function minimization problem, which is Lp-norm of residual of the linear equations system.
V. Stovba
doaj   +1 more source

Newton-type Methods for Minimax Optimization

open access: yes, 2020
Differential games, in particular two-player sequential zero-sum games (a.k.a. minimax optimization), have been an important modeling tool in applied science and received renewed interest in machine learning due to many recent applications, such as adversarial training, generative models and reinforcement learning.
Zhang, Guojun   +3 more
openaire   +2 more sources

Generative Models for Crystalline Materials

open access: yesAdvanced Materials, Volume 38, Issue 18, 25 March 2026.
Generative machine learning models are increasingly used in crystalline materials design. This review outlines major generative approaches and assesses their strengths and limitations. It also examines how generative models can be adapted to practical applications, discusses key experimental considerations for evaluating generated structures, and ...
Houssam Metni   +15 more
wiley   +1 more source

Existence of Periodic Solutions for a Class of Difference Systems with p-Laplacian

open access: yesAbstract and Applied Analysis, 2012
By applying the least action principle and minimax methods in critical point theory, we prove the existence of periodic solutions for a class of difference systems with p-Laplacian and obtain some existence theorems.
Kai Chen, Qiongfen Zhang
doaj   +1 more source

Diffusion‐MRI‐Based Estimation of Cortical Architecture via Machine Learning (DECAM) in Primate Brains

open access: yesAdvanced Science, Volume 13, Issue 14, 9 March 2026.
We present Diffusion‐MRI‐based Estimation of Cortical Architecture via Machine Learning (DECAM), a deep‐learning framework for estimating primate brain cortical architecture optimized with best response constraint and cortical label vectors. Trained using macaque brain high‐resolution multi‐shell dMRI and histology data, DECAM generates high‐fidelity ...
Tianjia Zhu   +7 more
wiley   +1 more source

Existence and multiplicity of solutions for a class of superlinear elliptic systems

open access: yesAdvances in Nonlinear Analysis, 2018
In this paper, we establish the existence and multiplicity of solutions for a class of superlinear elliptic systems without Ambrosetti and Rabinowitz growth condition. Our results are based on minimax methods in critical point theory.
Li Chun, Agarwal Ravi P., Wu Dong-Lun
doaj   +1 more source

Advances in Generative Models for Accelerated Discovery of New Materials

open access: yescScience, Volume 2, Issue 1, March 2026.
ABSTRACT The discovery of new materials can drive tremendous social and technological progress. However, the vastness of the material space makes comprehensive exploration computationally infeasible. This paper reviews the inverse design methods of generative models in materials science, aiming to discover customized materials based on specific ...
Yuan Jiang   +6 more
wiley   +1 more source

Evaluating cutpoints for the MHI-5 and MCS using the GHQ-12: a comparison of five different methods

open access: yesBMC Psychiatry, 2008
Background The Mental Health Inventory (MHI-5) and the Mental Health Component Summary score (MCS) derived from the Short Form 36 (SF-36) instrument are well validated and reliable scales. A drawback of their construction is that neither has a clinically
Fone David L   +3 more
doaj   +1 more source

Anomaly Detection and Localization With State‐of‐the‐Art Deep Learning Models to Support Quality Inspection in Car Manufacturing

open access: yesEngineering Reports, Volume 8, Issue 3, March 2026.
This work presents a deep learning framework for sealant inspection in automotive manufacturing, leveraging synthetic data to address the scarcity of real defects. Integrated with state‐of‐the‐art deep learning methods, the approach enhances anomaly detection and localization, demonstrating practical applicability and robustness under real‐world ...
Francesco Manigrasso   +3 more
wiley   +1 more source

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